Program, method, information processing apparatus

Abstract

A program, method, and information processing apparatus are provided for operating a computer having a processor that further reduces the burden on an expert for recording the consultation content of a consulter. 【Solution means】In a system, the program of the server 20 of the case management service for managing legal consultation cases causes a computer processor to extract information to be included in the work product from the information on the consultation content associated with the record of the case, generate a prompt for causing the work product to be output by a large language model using the extracted information, give the generated prompt to the large language model, receive a response from the large language model, and present the work product as the received response to the user.

Description

Technical Field

[0001] The present disclosure relates to a program, a method, and an information processing apparatus.

Background Art

[0002] Various stakeholders such as ordinary consumers and businesses are conducting procedures based on laws. Therefore, there are many opportunities to consult legal experts such as lawyers.

[0003] Patent Document 1 describes a technology that, with the problem of "providing legal consultation services at low cost", "interconnects providers and recipients of legal consultation services using an electronic network and provides legal consultation services via the electronic network".

[0004] According to the technology of Patent Document 1, it is said that "the transmission and reception of legal consultation service information between a provider terminal and a recipient terminal using an electronic network can be controlled", and "legal consultation services can be provided at lower cost".

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] After an expert hears the consultation content from the client, organizes the consultation content, clarifies the legal points, and constructs claims corresponding to the points, legal documents such as pleadings and answer briefs are created. In some cases, a contract is also created based on the content agreed upon between the parties. The expert may create a legal document, which is a specific deliverable, while referring to samples of pleadings, previously created pleadings, etc., or referring to the templates of contracts. As a result, compared with starting from scratch, since the work can be started from a state where the form of the document is grasped, it is possible to reduce the workload to a certain extent. However, the expert needs to create deliverables according to the individual circumstances of each case.

[0007] Therefore, there is a need for a technology that can make it even easier for an expert to create a deliverable according to the circumstances of an individual case.

Means for Solving the Problem

[0008] According to an embodiment shown in the present disclosure, a program for operating a computer including a processor is provided. In the storage unit, each of the consultation contents from the client is configured to be managed as a record of a case. The program causes the processor to perform steps of extracting information to be included in the deliverable from the information of the consultation content associated with the record of the case, generating a prompt for outputting the deliverable by a large language model using the extracted information, providing the generated prompt to the large language model, receiving a response from the large language model, and presenting the deliverable as the received response to the user.

Advantages of the Invention

[0009] According to the present disclosure, it is possible to make it even easier for an expert to create a deliverable according to the circumstances of an individual case.

Brief Description of the Drawings

[0010]

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Embodiments for Carrying Out the Invention

[0011] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In the following description, the same parts are denoted by the same reference numerals. Their names and functions are also the same. Therefore, detailed descriptions thereof will not be repeated.

[0012] <Outline of Embodiment> <1.1 Overall Configuration Diagram of System> FIG. 1 is a diagram showing the configuration of system 1.

[0013] The system 1 shown in FIG. 1 includes a server 20 for a case management service that manages legal consultation cases, a user terminal 10, a server 91 for a case law search service, a server 92 for a statute search service, a server 93 for a book browsing service, a server 94 for an information media service, a server 95 for an artificial intelligence (large language model) service (hereinafter sometimes referred to as "the server 95 for the large language model service"), a server 96 of a business operator, a server 97 of an SNS, and a user terminal 10A. These devices are communicatively connected via a network 80.

[0014] In the illustrated example, the terminals used by the users of the case management service provided by the server 20 are shown as the terminal 10, the terminal 10A, etc., but each user operates a terminal.

[0015] In the present embodiment, each device (terminal device, server, etc.) can also be regarded as an information processing device. That is, the aggregate of each device can be regarded as one "information processing device", and the system 1 may be formed as an aggregate of a plurality of devices. The way of distributing the plurality of functions required to implement the system 1 according to the present embodiment for one or a plurality of hardware can be appropriately determined in view of the processing capabilities of each hardware and / or the specifications required for the system 1.

[0016] The terminal 10 is a device operated by the user. In this embodiment, it is assumed that a user who is an expert in providing consultations on laws operates the terminal 10. The expert user creates legal documents such as contracts, warning letters, response letters, pleadings, and pleadings according to the content of the consultation. The terminal 10 and the terminal 10A have the same functional configuration. The terminal 10 is realized, for example, as follows. · Handheld portable terminals such as smartphones and tablets · Desktop PCs (Personal Computers), laptop PCs · Wearable terminals (such as wristwatch type and glasses type) worn by the user The terminal 10 includes a communication IF (Interface) 12, an input device 13, an output device 14, a memory 15, a storage 16, and a processor 19.

[0017] The communication IF 12 is an interface for inputting and outputting signals so that the terminal 10 can communicate with an external device.

[0018] The input device 13 is a device for receiving input operations from the user (for example, pointing devices such as touch panels, touch pads, and mice, keyboards, etc.).

[0019] The output device 14 is a device for presenting information to the user (displays, speakers, etc.).

[0020] The memory 15 is for temporarily storing programs and data processed by programs and the like, and is a volatile memory such as a DRAM (Dynamic Random Access Memory), for example.

[0021] The storage 16 is for storing data, and is, for example, a flash memory or an HDD (Hard Disc Drive).

[0022] The processor 19 is hardware for executing an instruction set described in a program, and is composed of an arithmetic unit, registers, peripheral circuits, and the like.

[0023] The server 20 is a device for providing a service to manage cases that are units of legal consultation services to users. In this embodiment, the server 20 provides functions for receiving registration of information related to a case from the user of the terminal 10, summarizing the consultation content, investigating the arguments related to the consultation content, investigating precedents or books corresponding to the arguments, and creating legal documents. The server 20 provides a case management service by causing the server 95 of the artificial intelligence (large language model) service to generate information related to these functions based on the case information, and recording the generation result in the server 20 while responding to the user.

[0024] Also, in this embodiment, the server 20 is also a device for providing a legal consultation service to users. In this embodiment, the server 20 receives an input of a legal consultation in free text in a chat format from the user of the terminal 10, causes the server 95 of the artificial intelligence (large language model) service to generate an answer to the received legal consultation content, and provides a legal consultation service by responding to the user with the generation result. As users, there can be a person consulting and an expert responding to the consultation. Specifically, the server 20 provides a legal consultation service to the following users. · Users who perform legal work and answer legal consultations, such as the legal department of a business company · Users who do not necessarily specialize in legal work, such as the business department of a business company · Users who provide legal consultations as a business to clients as experts, such as a law firm Server 20 may receive a legal consultation request from a requester to an expert by matching a user who conducts legal consultation services as an expert, such as a law firm, with a user who requests legal consultation from an expert such as a business company or an individual. For example, the consultation content of the consultee may be reflected on a bulletin board that can be viewed by a third party, and the expert's answer may also be made public, or the consultation content of the consultee may not be disclosed to a third party and remain confidential, and the consultation may be conducted between the consultee and the expert. Server 20 accumulates such consultation content of the requester and the answer content of the expert.

[0025] Server 20 includes a communication IF22, an input / output IF23, a memory 25, a storage 26, and a processor 29.

[0026] The communication IF22 is an interface for inputting and outputting signals so that Server 20 can communicate with an external device.

[0027] The input / output IF23 functions as an interface for an input device that receives input operations from a user and an output device that presents information to the user.

[0028] The memory 25 is for temporarily storing programs and data processed by programs and the like, and is, for example, a volatile memory such as a DRAM (Dynamic Random Access Memory).

[0029] The storage 26 is for storing data, and is, for example, a flash memory or an HDD (Hard Disc Drive).

[0030] The processor 29 is hardware for executing an instruction set described in a program, and is composed of an arithmetic unit, registers, peripheral circuits, and the like.

[0031] The server 91 of the case search service has a case database and enables users to search for judgments made by courts and the like.

[0032] The server 92 of the statute search service has a statute database and enables users to search for statutes.

[0033] The server 93 of the book viewing service is a service that enables viewing of electronic contents such as magazines and books. For example, by having users pay a fixed fee periodically, they can view e-books in the legal field and the like.

[0034] The server 94 of the information media service provides a service for providing information. For example, it is a service that enables collection and viewing of blog posts, Q&A sites, news articles, IR information, and the like. The server 94 of the information media service accumulates information such as interpretations based on statutes and guidelines of public offices and the like prepared to publicize operation rules.

[0035] In addition to these, the server 94 of the information media service may also provide a service for collecting and providing the following types of information. · Whether or not it is a group that meets the conditions for contract cancellation, such as belonging to an antisocial force. For example, there may be a database of business operators and the like that meet the above conditions, or public information such as news articles. · The reputation of a group such as a business company, etc., where the customer has a negative reaction and it has been picked up and spread on news, SNS, etc. For example, on SNS, etc., information may have spread with a negative keyword and a certain number of impressions or more. · Information related to performance, such as sales, revenue (amount of profit, profit rate, etc.), evaluation results related to business continuity (continuing losses, bankruptcy possibility, bond rating, etc.). The server 95 of the large language model service is a server that executes language processing tasks using a language model constructed by learning processes including artificial intelligence (AI). An LLM (Large Language Model) is one that has pre-learned a large amount of data (such as text data), for example, web content on the Internet, or data accumulated in a predetermined database, and can execute various language processing tasks by being given a task.

[0036] The server 95 of the large language model service receives input of prompts by text, image, voice, etc., and generates and responds with an answer to the prompt. Examples of LLM include GPT-3 and GPT-4 developed by OpenAI, BERT developed by Google, etc.

[0037] The server 96 of the business operator is for the business operator to conduct business activities and accumulate data generated in the course of business. These data have viewing permissions set, and the availability of viewing is set according to the data for users belonging to the business operator and external users not belonging to the business operator.

[0038] The server 97 of the SNS provides a service that promotes communication between users, for example, a service where the content posted by each user can be viewed mutually. For example, there are services that can be viewed by Internet search etc. even without having a user account on the SNS, and services where the posts of each user can be viewed when having a user account.

[0039] <1.2 Functional Configuration of Server 20> Figure 2 is a diagram showing the configuration of server 20. As shown in Figure 2, server 20 exhibits functions as a communication unit 201, a storage unit 202, and a control unit 203.

[0040] The communication unit 201 performs processing for the server 20 to communicate with an external device.

[0041] The storage unit 202 stores various databases such as a user database 211, a chat consultation history database 212, an LLM usage history database 213, a prompt database 214, an expert consultation history database 215, and a case management database 216.

[0042] The user database 211 is a database that manages information of each user. Details will be described later.

[0043] The chat consultation history database 212 is a database that shows the history of a user consulting using the services provided by the server 20. Details will be described later.

[0044] The LLM usage history database 213 is a database that shows the history of the server 95 of the artificial intelligence service generating answers for the consultation content of the user. Details will be described later.

[0045] The prompt database 214 is a database that manages the templates of the prompts to be sent to the server 95 of the large language model service. Details will be described later.

[0046] The expert consultation history database 215 is a database that shows the history of a user who is a consulter consulting an expert. Details will be described later.

[0047] The case management database 216 is a database that manages cases that are the units of the business related to the consultation. Details will be described later.

[0048] The control unit 203 is realized by the processor 29 reading the program stored in the storage unit 202 and executing the instructions included in the program. By operating according to the program, the control unit 203 exhibits functions shown as a reception control module 2041, a transmission control module 2042, a user management module 2043, a chat consultation processing module 2044, an LLM usage module 2045, a learning processing module 2046, a matching processing module 2047, and a case management module 2048.

[0049] The reception control module 2041 controls the process in which the server 20 receives a signal from an external device according to a communication protocol.

[0050] The transmission control module 2042 controls the process in which the server 20 transmits a signal to an external device according to a communication protocol.

[0051] The user management module 2043 is a module for managing information of each user who uses the system 1. Specifically, the user management module 2043 receives registration of each user's information and updates the user database 211.

[0052] The chat consultation processing module 2044 is a program module that receives and responds to legal consultation inputs from users via chat.

[0053] Specifically, the chat consultation processing module 2044 receives the input of the consultation content from the user, causes the server 95 of the large language model service to generate an answer, and updates the chat consultation history database 212.

[0054] The LLM utilization module 2045 is a program module that generates a prompt based on the content of a consultation input by a user in free text, image, voice, etc., and generates an answer by sending the generated prompt to the server 95 of the large language model service.

[0055] Specifically, the LLM utilization module 2045 manages the text input by the user as a series, and updates the LLM utilization history database 213 based on the prompt sent to the server 95 of the large language model service and the response from the server 95 of the large language model service.

[0056] The learning processing module 2046 is a program module that trains a learned model to output an answer to a question based on data accumulated in the server 20 as a chat consultation history database 212 or the like.

[0057] The matching processing module 2047 is a program module that accepts an operation of a person seeking legal advice to request an expert and matches with an expert such as a lawyer.

[0058] The case management module 2048 is a program module that accepts registration of various information about a case, records it in a record, reads out the information recorded in the record, and performs a process of presenting it to the user.

[0059] The case management module 2048 gives a notice based on a deadline when a deadline is set for a case.

[0060] <1.3 Configuration of Terminal 10> FIG. 3 is a diagram showing the configuration of the terminal 10.

[0061] As shown in FIG. 3, the terminal 10 includes a plurality of antennas (antenna 111, antenna 112), a communication unit corresponding to each antenna (first communication unit 120, second communication unit 121), an input device 130 (including a touch-sensitive device 131), a display 132, an audio processing unit 140, a microphone 141, a speaker 142, a position information sensor 150, a camera 160, a motion sensor 170, a storage unit 180, and a control unit 190. The terminal 10 also has functions and configurations not particularly shown in FIG. 3 (for example, a battery for holding power, a power supply circuit for controlling the supply of power from the battery to each circuit, etc.). As shown in FIG. 3, each block included in the terminal 10 is electrically connected by a bus or the like.

[0062] The antenna 111 radiates a signal emitted by the terminal 10 as a radio wave. Further, the antenna 111 receives a radio wave from space and gives the received signal to the first communication unit 120.

[0063] Antenna 112 radiates the signal emitted by terminal 10 as radio waves. Also, antenna 112 receives radio waves from space and supplies the received signal to the second communication unit 121.

[0064] The first communication unit 120 performs modulation / demodulation processing and the like for transmitting and receiving signals via antenna 111 so that terminal 10 can communicate with other wireless devices. The second communication unit 121 performs modulation / demodulation processing and the like for transmitting and receiving signals via antenna 112 so that terminal 10 can communicate with other wireless devices. The first communication unit 120 and the second communication unit 121 are communication modules including a tuner, an RSSI (Received Signal Strength Indicator) calculation circuit, a CRC (Cyclic Redundancy Check) calculation circuit, a high-frequency circuit, and the like. The first communication unit 120 and the second communication unit 121 perform modulation / demodulation, frequency conversion, etc. of the wireless signals transmitted and received by terminal 10, and supply the received signals to the control unit 190.

[0065] The input device 130 has a mechanism for receiving a user's input operation. Specifically, the input device 130 is configured as a touch screen and includes a touch-sensitive device 131. The touch-sensitive device 131 receives the input operation of the user of terminal 10. The touch-sensitive device 131 detects the contact position of the user on the touch panel, for example, by using a capacitance-type touch panel. The touch-sensitive device 131 outputs a signal indicating the contact position of the user detected by the touch panel to the control unit 190 as an input operation.

[0066] The display 132 displays data such as images, videos, and texts according to the control of the control unit 190. The display 132 is realized by, for example, an LCD, an organic EL display, or the like.

[0067] The audio processing unit 140 performs demodulation of the audio signal. The audio processing unit 140 modulates the signal given from the microphone 141 and gives the modulated signal to the control unit 190. Also, the audio processing unit 140 gives the audio signal to the speaker 142. The audio processing unit 140 is realized by, for example, a processor for audio processing. The microphone 141 receives an audio input and gives an audio signal corresponding to the audio input to the audio processing unit 140. The speaker 142 converts the audio signal given from the audio processing unit 140 into audio and outputs the audio to the outside of the terminal 10.

[0068] The position information sensor 150 is a sensor that detects the position of the terminal 10, and is, for example, a GPS (Global Positioning System) module. The GPS module is a receiving device used in a satellite positioning system. In the satellite positioning system, signals from at least three or four satellites are received, and based on the received signals, the current position of the terminal 10 equipped with the GPS module is detected.

[0069] The camera 160 is a device that receives light by a light receiving element and outputs it as a photographed image. The camera 160 is, for example, a depth camera that can detect the distance from the camera 160 to the object to be photographed.

[0070] The motion sensor 170 includes an acceleration sensor, an angular velocity sensor, etc., and detects the movement of the terminal 10.

[0071] The storage unit 180 is composed of, for example, a flash memory or the like, and stores data and programs used by the terminal 10. Various information stored in the storage unit 180 will be described later.

[0072] The control unit 190 reads the program stored in the storage unit 180 and executes the instructions included in the program to control the operation of the terminal 10. The control unit 190 is, for example, an application processor. By operating according to the program, the control unit 190 functions as an operation reception unit 191, a transmission / reception unit 192, a data processing unit 193, a notification control unit 194, and a storage control unit 195.

[0073] The operation reception unit 191 performs a process of receiving a user's input operation on an input device such as the touch-sensitive device 131. Based on the information of the coordinates where the user touches the touch-sensitive device 131 with a finger or the like, the operation reception unit 191 determines the type of operation, such as whether the user's operation is a flick operation, a tap operation, a drag (swipe) operation, or the like.

[0074] The transmission / reception unit 192 performs a process for the terminal 10 to transmit and receive data to and from an external device such as the server 20 according to a communication protocol.

[0075] The data processing unit 193 performs a process of performing calculations on the data input by the terminal 10 according to a program and outputting the calculation results to a memory or the like.

[0076] The notification control unit 194 performs a process of displaying a display image on the display 132, a process of outputting sound to the speaker 142, and a process of generating vibration.

[0077] The storage control unit 195 controls the storage of data in the storage unit 180.

[0078] Explanation will be given for various information stored in the storage unit 180. In a certain aspect, the storage unit 180 stores each information such as user information 181.

[0079] The user information 181 is information of a user who uses the service of the server 20.

[0080] <2 Data Structure> Figure 4 is a diagram showing the data structure of the user database 211. The user database 211 includes an item "user ID", an item "name", an item "email address", an item "attribute", an item "business operator ID", an item "held qualification", an item "registration date", an item "status", an item "field", and an item "evaluation value".

[0081] The item "user ID" is information for identifying each user.

[0082] The item "name" is information indicating the name of the user.

[0083] The item "email address" is information on the email address as the contact information of the user.

[0084] The item "attribute" is information indicating the attribute of the user.

[0085] Specifically, the item "attribute" includes the following as the attribute of the user. · A person who consults on legal matters · An expert who answers in response to legal consultations. For example, a qualified person such as a lawyer The item "business operator ID" is information for identifying the organization to which the user belongs.

[0086] Specifically, the following organizations may exist as the information for identifying the organization to which the user belongs in the item "business operator ID". · Law firm · Business company · Individual (not as a person belonging to an organization, but may consult as an individual) The item "held qualification" is information indicating the qualification held by the user.

[0087] Specifically, the following qualifications may exist as the information for identifying the qualification held by the user in the item "held qualification". · National qualifications such as lawyers, patent attorneys, and certified public accountants · Qualifications recognized by organizations such as business operators and general incorporated associations The item "Registration Date" is information indicating the date and time when the user registered for the service.

[0088] The item "Status" is information indicating the status of the user regarding legal consultations.

[0089] Specifically, the item "Status" includes the following as the status of the user. · Under Consultation: A state where a user who is an expert can receive consultations from the consulters. · Consultation on Hold: A state where a user who is an expert is not receiving consultations. For example, it may be that no new consultations are being received because the number of consultations has reached a certain level or more. Server 20 changes the status of the user in the item "Status" according to the user's operation. The item "Field" is information indicating the field in which the user has expertise.

[0090] Specifically, the item "Field" includes information on each field classified as a field of legal consultation. For example, if server 94 of the information media service provides a service for introducing experts such as lawyers and classifies the fields of experts according to the classification of the consultation content (such as debt restructuring, traffic accidents, divorce, inheritance, etc.), it may include information on each of these classified fields. Server 20 may update the user database 211 according to the operation of the user designating the field, or a user who is an expert may set the field of the user who is an expert by referring to the field of the legal consultation based on the achievements corresponding to the legal consultation.

[0091] The item "Evaluation Value" is information indicating the evaluation value obtained by evaluating the mode of the user's legal consultation.

[0092] Specifically, the item "Evaluation Value" includes the following as the evaluation value of the user. · Evaluation Value as an Expert: The evaluation value evaluated based on the achievements (number of cases, frequency, etc.) of answering consultations from the consulters. · Evaluation value as a consulter: An evaluation value evaluated based on the achievements of the consulter consulting an expert and being appointed by the expert, the achievements of the consulter sorting out (inputting the consultation content) the consultation content through the legal consultation service provided by the server 20, etc. FIG. 5 is a diagram showing the data structure of the chat consultation history database 212. The chat consultation history database 212 includes an item "consultation thread ID", an item "consulter user ID", an item "post ID", an item "post content", an item "related posts", an item "post date and time", an item "search target database", an item "search result", an item "LLM output", an item "answer", and an item "user evaluation".

[0093] The item "consultation thread ID" is information for identifying the thread of each consultation in which the user consults by chat in the legal consultation service provided by the server 20.

[0094] The item "consulter user ID" is information for identifying the user who conducts the consultation.

[0095] Specifically, the item "consulter user ID" corresponds to the item "user ID" in the user database 211.

[0096] The item "post ID" is information for identifying each post associated with the thread.

[0097] The item "post content" is information indicating the content posted by the user.

[0098] The item "related posts" is information indicating other posts related to the post indicated by the item "post ID" for a plurality of posts managed in the thread.

[0099] Specifically, the item "Related Posts" is information that identifies the most recent post made by the user among a plurality of posts managed in a thread. In this way, each time the user posts a consultation in the thread indicated by the item "Consultation Thread ID", by associating it with the "Post ID" of the most recent post already made and managing it in the chat consultation history database 212, the order of a series of posts in the thread can be managed.

[0100] The item "Post Date and Time" is information indicating the timing when the user made the post.

[0101] Specifically, the item "Post Date and Time" may be the timing when a question was received from the user in free text or the like.

[0102] The item "Database to be Searched" is information that identifies the database to be referred to by search when generating an answer by the server 95 of the large language model service.

[0103] Specifically, the item "Database to be Searched" may include the following information as the database to be referred to. · Information that can be obtained by search on the Internet · Information provided by the server 91 of the case search service · Information provided by the server 92 of the statute search service · Information provided by the server 93 of the book viewing service · Information provided by the server 94 of the information media service · Information provided by the server 95 of the artificial intelligence (large language model) service · Information provided by the server 96 of the business operator · Information provided by the server 97 of the SNS The item "Search Results" is information indicating the search results obtained by searching the database to be referred to based on the user's post content.

[0104] Specifically, the item "Search Results" includes the results of a search performed by server 20 based on the user's posted content indicated in the item "Post ID" as follows. · Extract words from the user's posted content and use them as search keys. At this time, based on the legal terms recorded in a legal term database (not shown), legal terms are used as search keys without further decomposition into words. · Analyze the meaning of the user's posted content and vectorize it using a method such as Word2Vec. The documents in the database to be referenced are also vectorized in the same way, and the documents stored in the database are searched based on the proximity of the vectors. The item "LLM Output" is information indicating the result generated by server 95 of the large language model service based on the user's post.

[0105] Specifically, the item "LLM Output" includes the results of having server 95 of the large language model service generate answers as follows. · Results obtained by having server 95 of the large language model service summarize the results of referring to each database shown in the item "Search Results" · Results obtained by having server 95 of the large language model service generate answers with backgrounds such as "judgment by users in the legal department" included in the prompt when generating answers The item "Answer" is information indicating the answer presented to the user.

[0106] Specifically, for the item "Answer", the server 95 of the large language model service may present the user with an answer that includes the results generated by server 95 and the information generated by server 20 as follows. · An answer that includes a link that allows the source information of the results summarized by server 95 of the large language model service to be referenced · An answer in which server 20 adds the original text of the articles recorded in the statute database, etc. and the cases recorded in the case database to the results summarized by server 95 of the large language model service The item "User Evaluation" is information indicating the user's evaluation of the answer presented by server 20.

[0107] Figure 6 is a diagram showing the data structure of the LLM usage history database 213. The LLM usage history database 213 includes an item "usage ID", an item "consultation thread ID", an item "post ID", an item "prompt", an item "LLM output result", an item "usage date and time", and an item "case ID".

[0108] When the server 20 provides a legal consultation service to the user, the server 20 may cause the server 95 of the large language model service to execute a task using the post input by the user. In addition, in response to the registration of case data in the case management service provided by the server 20, the server 95 of the large language model service may generate information.

[0109] The item "usage ID" is information for identifying each history of answers generated by the server 95 of the large language model service.

[0110] The item "consultation thread ID" is information for identifying the thread in which the user consults in the legal consultation service provided by the server 20.

[0111] Specifically, the item "consultation thread ID" corresponds to the item "consultation thread ID" in the chat consultation history database 212.

[0112] The item "post ID" is information for identifying the post of the question input by the user, which is the target for generating an answer by the server 95 of the large language model service.

[0113] Specifically, the item "post ID" corresponds to the item "post ID" in the chat consultation history database 212.

[0114] The item "prompt" is information indicating the content of the prompt applied when transmitting to the server 95 of the large language model service.

[0115] Specifically, the item "prompt" may include the content of the prompt defined as follows and sent to the server 95 of the large language model service. · Based on the content of the question input by the user, add the search results obtained by searching each database (the item "search results" in the chat consultation history database 212) to the prompt template defined in the prompt database 214 described later, and use it as the prompt to be sent to the server 95 of the large language model service. · Apply the data registered in association with the case in the case management database 216 to the prompt template defined in the prompt database 214 described later, and use it as the prompt to be sent to the server 95 of the large language model service. The item "LLM output result" is information indicating the content output by the server 95 of the large language model service by sending a prompt to the server 95 of the large language model service.

[0116] The item "usage date and time" is information on the date and time when the server 95 of the large language model service generated an answer.

[0117] The item "case ID" is information for identifying each case managed in the case management database 216 described later.

[0118] Figure 7 is a diagram showing the data structure of the prompt database 214. The prompt database 214 includes an item "prompt ID", an item "operator ID", an item "prompt template", an item "usage permission setting", and an item "availability".

[0119] The item "prompt ID" is information for identifying each prompt.

[0120] The item "operator ID" is information for identifying the organization that uses the prompt.

[0121] Specifically, the item "operator ID" corresponds to the item "operator ID" in the user database 211.

[0122] The item "prompt template" is information indicating the content of the prompt template.

[0123] Specifically, the item "prompt template" may include a prompt template containing the following content. · Summarize the information entered by the user in the legal consultation service or the case management database 216. For example, it may be summarized within a certain number of characters. · Arrange the facts related to the consultation content in chronological order in the text of the consultation content of the consulter (for example, the text obtained by converting the voice data of the consultation content into characters by character recognition). · Explain the correlation of the people appearing in the consultation content in the text of the consultation content of the consulter in an article. · Extract the next action (next action) from the transcript of the conversation between the consulter and the expert. For example, from the transcript of the conversation, as the content referring to the next action, keywords such as "summary", "next action", and "next time" are specified, and the content of the speech associated with the keyword may be used as the next action. Also, when there are keywords indicating the next action to be taken, such as "next action", "summary", and "work until next time" in the minutes data, the minutes may be referred to to extract the next action. · Extract what the consulter values as the consultation content and the concerns of the consulter based on the content of the conversation of the consulter and the result of determining the emotion from the voice data. · Extract the concerns of the consulter from the consultation content of the consulter. · Identify the legal arguments from the consultation content of the consulter and the concerns of the consulter. For example, it may be possible to extract words from the consultation content and the concerns of the consulter to identify the arguments. Also, on the server 20, a list of keywords is maintained for each argument, and the words extracted from the consultation content and concerns of the consulter are compared with the list of keywords for each argument to identify the arguments. · Summarize case law, statutes, and descriptions in books regarding legal arguments. For example, identify legal arguments from the concerns of the person seeking advice, search the servers of a case law search service 91, a statute search service 92, a book browsing service 93, and other various databases using these arguments, and summarize the search results. It may also be possible to extract the basis articles corresponding to the arguments. · Search for case law. Point out changes in the interpretation of case law corresponding to the argument. For example, when amending and indicating the original judgment, display the amended parts in the judgment of the higher court against the original judgment. · Compare the past interpretation and the latest interpretation of the interpretation of case law and point out the differences. For example, search for specific examples of the argument and contrast the interpretation recorded in books published in the past with the latest interpretation. · Create legal-related documents such as contracts, term sheets, warning letters, response letters, pleadings, pleadings, and preparatory documents based on the information stored in the case management database 216. For example, it may be possible to create a pleading by referring to the information of the parties. · Output the counterarguments of the assumed counterpart to the claims related to the argument for legal documents such as pleadings and preparatory documents. For example, search for past case law regarding the argument, and refer to these past case laws to generate the assumed counterarguments on the server 95 of the large language model service. · Output the citation relationship of the terms of the contract according to a predetermined format. For example, it may be possible to output the terms of the citation source and the citation destination of the contract in pairs. · Generate a list of the materials and evidence registered in the case management database 216. · Generate a list of the evidence mentioned in the data such as pleadings and preparatory documents registered in the case management database 216. · A form for generating an answer on the server 95 of the large language model service. For example, there are those that specify the items to be included in the answer, and there may be a prompt that instructs to generate an answer along the specified items. Such items may include legal arguments, a list of stakeholders, generating answers separately for each stakeholder, the advantages and disadvantages of the stakeholders, etc. · An instruction to generate a summary for data that is not publicly available to third parties and is referenced by users belonging to an organization, such as the data stored in the operator's server 96 The item "Usage Permission Setting" is information indicating the range of users who have the right to generate answers on the server 95 of the large language model service using prompts.

[0124] Specifically, the item "Usage Permission Setting" may include information on permissions set as follows. · When generating a summary for data that is not publicly available to third parties, such as the data stored in the operator's server 96, users who do not belong to the organization do not have permission, and users who belong to the organization are given permission. · Set permissions according to the user's department (for example, generate a summary for data that can be referenced by specific departments such as business planning). · Set permissions according to the user's position (for example, generate a summary for data that can be referenced by users in specific positions such as management). The item "Availability" is information indicating whether to use the prompt template as a target for use.

[0125] Specifically, the item "Availability" includes information on whether to permit or not permit the use of the prompt template. For example, the server 95 of the large language model service may update the prompt template for generating better answers and stop the use of the previous prompt template.

[0126] Figure 8 is a diagram showing the data structure of the expert consultation history database 215. The expert consultation history database 215 includes an item "Expert Consultation ID", an item "Chat Consultation ID", an item "Consultation Content", an item "Field", an item "Expert ID", an item "Consultation Date and Time", and an item "Assignment Result".

[0127] The item "Expert Consultation ID" is information for identifying each request for a user to consult an expert.

[0128] Specifically, the item "Expert Consultation ID" corresponds to the item "Consultation with Expert" in the chat consultation history database 212.

[0129] The item "Chat Consultation ID" is information for identifying each consultation that the consultor had in a chat in the legal consultation service provided by the server 20 when the consultor requests a consultation from an expert.

[0130] Specifically, the item "Chat Consultation ID" corresponds to the item "Chat Consultation ID" in the chat consultation history database 212.

[0131] The item "Consultation Content" is information indicating the content of the consultation requested by the consultor from an expert.

[0132] Specifically, the item "Consultation Content" includes information on the content of the consultation request entered by the consultor at the stage when the consultor performs an operation to request a consultation from an expert. The server 20 obtains the content entered by the consultor into the chat system by referring to the chat consultation history database 212, and causes the server 95 of the large language model service to summarize at least one of the consultation content of the consultor or the answer generated by the server 95 of the large language model service for the question, and the summarized result may be used by the consultor as information on the content of the request when the consultor requests a consultation from an expert. Thereby, for the consultor, it is possible to make it even easier to input the content to be requested from an expert.

[0133] The item "Field" is information indicating the field of the consultation set for the consultor's request for consultation from an expert.

[0134] Specifically, the item "Field" includes information on the field set by the server 20 or the user (consultor or expert).

[0135] In addition, for example, the server 20 may identify the field of consultation by extracting legal terms included in the content of the user's question in the chat consultation history database 212 and the answer generated by the server 95 of the large language model service.

[0136] The item "Expert ID" is information for identifying the expert who responded to the consultation request from the consulter.

[0137] Specifically, the item "Expert ID" corresponds to the item "User ID" in the user database 211.

[0138] The item "Consultation Date and Time" is information on the date and time when the consultation request from the consulter to the expert was registered.

[0139] The item "Acceptance Result" is information indicating whether the expert has accepted the consultation request from the consulter.

[0140] Specifically, the item "Acceptance Result" includes the following information. · Accepted: The expert has reached the acceptance of the consultation request from the consulter (for example, the expert has registered that they have reached the acceptance). · Not Accepted: The expert responded to the consultation request from the consulter but did not reach the acceptance (timed out after a certain period from the consultation date and time, and the expert has registered that they did not reach the acceptance). Figure 9 is a diagram showing the data structure of the case management database 216. The case management database 216 includes an item "Case ID", an item "Consulting User ID", an item "Expert User ID", an item "Consultation Audio Data", an item "Consultation Content Memo", an item "Consultation Date and Time", an item "AI Summary of Consultation Content", an item "AI Argument Extraction", an item "AI Research Result", an item "Document Data", and an item "Legal Document Data".

[0141] The item "Case ID" is information for identifying each case.

[0142] The item "Consultant User ID" is information that identifies the user who is the consultant.

[0143] Specifically, the item "Consultant User ID" corresponds to the item "User ID" in the user database 211.

[0144] The item "Expert User ID" is information that identifies the user who is the expert.

[0145] Specifically, the item "Expert User ID" corresponds to the item "User ID" in the user database 211.

[0146] The item "Consultation Voice Data" is the voice data of the conversation when the consultant consults an expert.

[0147] Specifically, the item "Consultation Voice Data" may include the following. · The voice data itself · The text transcription data obtained by performing character recognition processing on the voice data · The data of the speaker's emotion obtained by performing speaker and emotion determination processing on the voice data The item "Consultation Content Memo" is the memo information input by the expert or the consultant.

[0148] The item "Consultation Date and Time" is the information of the time when the consultation from the consultant to the expert was made.

[0149] Specifically, the item "Consultation Date and Time" is The item "Consultation Content AI Summary" is the information of the result summarized by the server 95 of the large language model service for the data of the consultation content of the consultant.

[0150] Specifically, the item "Consultation Content AI Summary" includes the result summarized by the server 95 of the large language model service based on the text transcription data of the voice data related to the conversation between the consultant and the expert.

[0151] The item "AI Argument Extraction" is the information of the arguments identified by the server 95 of the large language model service for the data of the consultation content of the consulter.

[0152] The item "AI Research Result" is the information of the result summarized by the server 95 of the large language model service for the information such as case laws, statutes, interpretations, and explanations regarding the arguments.

[0153] Specifically, the item "AI Research Result" includes the result of summarizing the search results obtained by searching various databases such as the server 91 of the case search service, the server 92 of the statute search service, and the server 93 of the book browsing service for the arguments by the server 95 of the large language model service.

[0154] The item "Document Data" is the information provided by the consulter regarding the case, the information collected by experts, etc.

[0155] Specifically, the item "Document Data" includes information such as documents not disclosed to the other party, documents publicly released, and evidence submitted in legal procedures.

[0156] The item "Legal Document Data" is the data of the documents submitted in legal procedures.

[0157] Specifically, the item "Legal Document Data" includes the following types of document data. · Contract · Term Sheet · Warning Letter · Response Letter (responding to the warning letter) · Complaint · Answer · Preparation Document <3 Operations (First Embodiment)> Figure 10 is a flowchart showing the process flow in which the user requests a consultation from an expert through a legal consultation in chat and the expert accepts the appointment.

[0158] In step S1021, the server 20 presents an operation screen for receiving input of questions about legal consultations to the user who is the consulter.

[0159] In step S1011, the terminal 10 displays an answer generated by the server 95 of the large language model service for the question of legal consultation received from the user. The terminal 10 receives from the user an operation of requesting consultation with an expert about the legal consultation related to the question on the operation screen.

[0160] The server 20 is configured to store information of experts such as lawyers who can answer legal consultations in the user database 211. The server 20 refers to the chat consultation history database 212 and extracts candidates for experts corresponding to the consultation according to the request based on the content of the consultation related to the user's request, the answer generated by the server 95 of the large language model service, and the information of the experts. For example, the server 20 may identify the field related to the consultation content from the terms included in the consultation content and the content of the generated answer, and extract lawyers specializing in the field from the user database 211.

[0161] The terminal 10 displays the experts extracted by the server 20 as candidates for requesting consultation. The terminal 10 presents the candidates for the extracted experts to the user together with the information of the experts (such as name, field of expertise, etc.).

[0162] The terminal 10 may receive input of conditions for selecting an expert from the user. For example, there may be a case where it is desired to further narrow down the candidates for experts extracted by the server 20 or search for experts different from the extracted experts. The server 20 may extract candidates for experts according to the conditions received from the user and the candidates for experts.

[0163] The terminal 10 may also accept an operation from the user to publicly disclose questions about the user's legal consultation so that a third party can view them. The server 20 may also make the questions about the legal consultation viewable by a third party in response to the public disclosure operation. When making the questions and answers viewable by a third party, the server 20 may generate an answer by instructing the server 95 of the large language model service not to include the user's personal information when generating the answer.

[0164] In step S1023, the server 20 outputs to the expert user, based on the chat consultation history database 212, that there is a consultation request from the consulter and the content based on the answer generated by the server 95 of the large language model service for the consultation.

[0165] Here, the server 20 may also generate a prompt instructing to generate an answer along the specified items for the question of the user who is the consulter, and cause the server 95 of the large language model service to generate an answer. For example, the server 20 may generate a prompt instructing to generate an answer by organizing as follows as the specified items. · Items of interested parties · Items of time information · Items of arguments · Items of monetary value related to legal consultation (such as how much the damages are, etc.) · Items of relevant laws and regulations, case laws The server 20 sends a prompt instructing to generate an answer along the specified items as described above to the server 95 of the large language model service, receives the generated answer, and updates the chat consultation history database 212.

[0166] Server 20 may output content based on the answers generated by experts in accordance with the specified items. For example, Server 20 manages the case management database 216 used by experts, and creates a prompt to generate answers in accordance with the specified items as described above so as to match the items of the records for managing each case in the case management database 216. Thereby, Server 20 may update the case records in the case management database 216 based on the results generated by Server 95 of the large language model service.

[0167] Server 20 evaluates the user's consultation based on the questions input by the user and the answers generated by Server 95 of the large language model service, which are held in the chat consultation history database 212, and updates the item "acceptance possibility" in the chat consultation history database 212 based on the evaluation result.

[0168] Server 20 may refer to the chat consultation history database 212 and output to an expert the score for evaluating the consultation of the user who made the request regarding the request of the user who is the consulter.

[0169] Server 20 may refer to the expert consultation history database 215 and evaluate the possibility of acceptance according to the record of whether the legal consultation of the consulter has led to acceptance by an expert.

[0170] Server 20 may refer to the chat consultation history database 212 and evaluate the possibility of acceptance based on at least any one of the data volume of the questions input by the user regarding the legal consultation, whether the large language model has succeeded in answering, and whether the answers generated by the large language model have a data volume above a certain level.

[0171] Server 20 may refer to the chat consultation history database 212 and preferentially output to an expert the legal consultations regarding requests that are evaluated to have a possibility of acceptance above a certain level.

[0172] In step S1025, when the server 20 receives an operation from an expert to respond to a request from a client, it updates the expert consultation history database 215 and notifies the user who is the client.

[0173] In step S1013, the terminal 10 presents to the user that the expert has responded to the request.

[0174] As described above, an example has been explained in which an expert receives a consultation from a client by matching with a client who uses a legal consultation service and registers the information of the case in the case management database 216. However, it is not limited to this, and there may be a case where an expert receives an inquiry from a client and manages the case in the case management database 216.

[0175] FIG. 11 is a diagram showing the flow of processing for summarizing the consultation content from a client by a large language model and associating it with a record of a case.

[0176] In step S1121, the case management module 2048 of the server 20 outputs an operation screen for managing a case to the terminal 10.

[0177] In step S1111, the terminal 10 receives an operation to upload consultation data indicating the consultation content from a client on the operation screen. The consultation data is, for example, voice data, recording data of a meeting, a memo input during an interview between a client and an expert, etc.

[0178] In step S1123, the case management module 2048 of the server 20 receives the consultation data from the terminal 10 and registers it in the record of the case in the case management database 216.

[0179] The case management module 2048 receives, as consultation data, voice data indicating the content of the consultation. When the case management module 2048 receives the voice data, it performs character recognition processing to obtain the transcribed data obtained by transcribing the voice data. The case management module 2048 registers the transcribed data as case information by associating it with the counselor and storing it in the records of the case management database 216.

[0180] The case management module 2048 performs speaker determination and sentiment determination processing on the voice data, and further stores at least any one of the information on the result of determining the speaker, the information on the result of determining the sentiment, and the information on the timing when the consultation from the counselor occurred in the case management database 216.

[0181] In step S1125, the case management module 2048 of the server 20 transmits a prompt for summarizing the consultation content indicated in the consultation data along a predetermined item to the server 95 of the large language model service. Here, the predetermined item may correspond to each subfield indicated in the case management database 216.

[0182] The case management module 2048 may obtain the result of summarizing the consultation content by giving a prompt to the server 95 of the large language model service so as to summarize the consultation content indicated in the consultation data along a predetermined item.

[0183] The case management module 2048 may obtain the result of summarizing in chronological order by giving a prompt to the server 95 of the large language model service to sort and organize the consultation content included in the consultation data in chronological order as a prompt.

[0184] For example, the case management module 2048 may cause the server 95 of the large language model service to generate a text in which the consultation content is organized in chronological order by giving the following prompt to the server 95 of the large language model service. ·Identify the date included in the transcription of the consultation content and extract the consultation content (facts, etc.) associated with the date (for example, statements such as "There was ~~~ around ~~ year"). ·Based on the expression of the past tense of the verb, extract the facts that occurred in the past (for example, from the statement content such as "Loaned money", determine that it is an expression in the past tense of "loaned" and extract it as a fact that occurred in the past). ·When there is no word indicating the time period for a fact, treat it as a fact of the time period detected most recently. ·Extract the relative time period by detecting the demonstrative pronoun and the word indicating the time period (for example, if there is a statement such as "Two months before that", detect that it is a time period that is relatively before or after compared to the time period represented by the demonstrative pronoun (for example, the most recently detected time period). For example, if it is "Two months before that", it indicates a time period further before than the time period indicated by the demonstrative pronoun). ·When there is no demonstrative pronoun, regard it as a fact based on the time point when the consultation took place. In step S1127, the case management module 2048 of the server 20 obtains the result of summarizing the consultation content from the server 95 of the large language model service and registers it in the record of the case for the counselor in the case management database 216. The case management module 2048 associates the consultation content summarized along with the predetermined items by the server 95 of the large language model service with the counselor and stores it in the case management database 216 so that the experts responding to the consultation from the counselor can refer to it.

[0185] When the case management module 2048 obtains the summarized result sorted in chronological order from the server 95 of the large language model service, it stores it in the case management database 216 in association with the counselor.

[0186] In the case management database 216, each consultation from the counselor is managed as a case including predetermined management items. The case management module 2048 may associate and store each item of the consultation content summarized along with the predetermined items with each management item managed as a case in the case management database 216.

[0187] In the case management database 216, as predetermined management items, at least any one of the consultation content from the consulter, the next action which is the action to be taken next, and the concerns of the consulter is managed as a case. The case management module 2048 may obtain the summarized result by giving a prompt to the server 95 of the large language model service so as to summarize at least any one included in the predetermined management items as a predetermined item.

[0188] The case management module 2048 may extract the concerns of the consulter based on the voice data of the consultation content of the consulter and the information of the result of determining the emotion, and store the information of the concerns of the consulter as the information of the case in the case management database 216. For example, based on the result of determining the emotion, in the following cases, it may be extracted as the concerns of the consulter. · The text corresponding to the voice of the consultation content of the consulter while the emotion is determined to be "anger" or "anxiety" · The text corresponding to the voice of the consultation content of the consulter before and after the evaluation value of evaluating the emotion changes to a certain level or more (the emotion fluctuates) · The text corresponding to the voice in a state where the volume of the voice data of the consulter is a certain level or more (it may also include before and after that) (such as a loud voice) · When the text conversion of the voice data of the consulter includes a statement indicating something to be concerned about. For example, as statements, "worried", "want to do something about it" (a statement with the intention of solving the problem), "hate", "angry" (a statement showing a negative emotional reaction), "don't want to be ~~" (a statement with the intention of avoiding falling into a specific behavior or a specific state), "is it okay to do ~~~" (a statement with the intention of confirming whether it is okay to shift to a specific behavior or a specific state. For example, "is it okay to negotiate directly with the other party"), etc. may exist · Among the keywords appearing in the consulter's speech, those with the number of appearances being a certain level or more, or those with a high frequency (because they are repeated, there may be concerns about the matters corresponding to the keywords) The case management module 2048 may cause the server 95 of the large language model service to extract the information on the concerns of the interlocutor by providing the server 95 of the large language model service with a prompt, the voice data of the interlocutor, the speech-to-text conversion of the voice data, the result of sentiment determination, etc., so as to extract the concerns of the interlocutor as described above.

[0189] In step S1129, the case management module 2048 of the server 20 outputs the information on the record of the case to the terminal 10.

[0190] In step S1113, the terminal 10 displays the information on the record of the case.

[0191] FIG. 12 is a diagram showing the process flow of generating document data by receiving an operation of decomposing and rearranging the consultation content from the interlocutor.

[0192] In step S1221, the case management module 2048 of the server 20 outputs an operation screen to the terminal 10, which decomposes the consultation content of the interlocutor and displays each as an object that the user can rearrange.

[0193] In step S1211, the terminal 10 displays the information on the record of the case. The terminal 10 displays the operation screen and receives from the user an operation of rearranging each object corresponding to the consultation content.

[0194] In step S1223, the case management module 2048 of the server 20 provides the server 95 of the large language model service with a prompt for generating a text in chronological order for the consultation content shown in each object based on the order in which the objects are rearranged in response to the operation of rearranging the objects. Thereby, the case management module 2048 obtains a summarized result sorted in chronological order for the consultation content from the interlocutor and registers it in the case management database 216. The case management module 2048 outputs the result summarized in chronological order to the terminal 10.

[0195] In step S1213, the terminal 10 displays the results summarized by the large language model service server 95, which are sorted in time series.

[0196] FIG. 13 is a diagram showing the flow of a process of expressing a person correlation diagram in text.

[0197] In step S1311, the terminal 10 displays an operation screen and accepts upload of an image of a person correlation diagram related to the consultation content from the user.

[0198] In step S1323, the case management module 2048 of the server 20 transmits a prompt for generating a text showing the correlation between persons to the large language model service server 95 based on the received image of the person correlation diagram.

[0199] Here, the person correlation diagram is a diagram showing the relationships between the characters who appear.

[0200] Specifically, the case management module 2048 gives the large language model service server 95, as a prompt, a rule for interpreting the image of the person correlation diagram, thereby causing the large language model service server 95 to generate a text showing the relationships between persons.

[0201] For example, the prompt includes the following instruction content. · Figures such as circles and rectangles represent the characters who appear. If the figure contains a person's name or image, the figure represents the character who appears · If text of a person's name is placed near the figure, the figure represents the character who appears, and the text represents the name of the character who appears · An arrow connecting figures such as circles and rectangles represents the subject who performed the action and the recipient who received the action. · If text is arranged in association with the arrow, the text indicates the content of the action. · If a line connecting figures such as circles and rectangles is an equal sign, it simply indicates the relationship between persons. · If text is arranged in association with the equal sign line, the text indicates the content of the relationship between people. · Based on the above rules, please describe the given figure in words. In step S1325, the case management module 2048 of the server 20 obtains the result of generating a text showing the correlation of people from the server 95 of the large language model service, and registers it in the record of the case for the counselor in the case management database 216.

[0202] In step S1327, the case management module 2048 of the server 20 outputs a text showing the correlation of people to the terminal 10 as information of the record of the case in the case management database 216.

[0203] In step S1313, the terminal 10 displays a text showing the correlation of people as information of the record of the case.

[0204] Figure 14 is a diagram showing the flow of a process of presenting questions to the user to increase the resolution of information about people.

[0205] In step S1411, the terminal 10 accepts the upload of the voice data of the consultation content.

[0206] In step S1423, the case management module 2048 of the server 20 obtains the speech-to-text of the voice data of the consultation content and registers it in the record of the case in the case management database 216.

[0207] In step S1425, when the case management module 2048 of the server 20 identifies a word indicating a person in the speech-to-text data, it presents a question asking about the relationship between the identified person and other characters involved in the consultation content to the user of the counselor or expert, and accepts the input of the answer.

[0208] For example, when the case management module 2048 identifies a word consisting of a proper noun and an honorific (such as "san" which is an honorific added to a name) in the transcribed data, it may also identify the word as indicating a person. Further, the case management module 2048 may identify the word indicating a person by collating with a dictionary indicating personal names in the transcribed data.

[0209] In step S1413, the terminal 10 receives, from the user, an answer to a question asking about the relationship between people.

[0210] In step S1427, the case management module 2048 of the server 20 registers the answer regarding the relationship between people in the record of the case in the case management database 216. The case management module 2048 outputs the information of the record including the sentence indicating the relationship between people to the terminal 10.

[0211] In step S1415, the terminal 10 displays the information of the record of the case.

[0212] <4 Screen example (First embodiment)> FIG. 15 is an example of an operation screen for a counselor to request consultation from an expert.

[0213] The operation screen 1200 is a screen for receiving legal consultations in chat form from a user who is a counselor.

[0214] The account display area 1202 is an area for displaying the information of the account of the user who is a counselor.

[0215] The chat display area 1204 is an area for displaying the questions input in the legal consultation and the answers generated by the server 95 of the large language model service.

[0216] The navigation display area 1212 is an area for displaying information to assist the user in consulting in chat form about the legal consultation.

[0217] In the illustrated example, the navigation display area 1212 presents to the user the fact that an answer has been generated for the user (the "AI answer display area 1222") and the content of the operation for making a request to an expert.

[0218] The chat input reception unit 1214 is an area that receives input of a question by the user entering text.

[0219] As shown in the figure, the chat input reception unit 1214 may display information suggesting the content to be entered in order to prompt the user to enter a question sentence. This corresponds to step S1011 in FIG. 10 and the like.

[0220] The AI answer display area 1222 is an area that displays the answer generated by the server 95 of the large language model service for the question sentence entered by the user.

[0221] The request display area 1224 is an area that displays a screen for requesting an expert regarding legal consultation.

[0222] The request display area 1224 corresponds to step S1011 in FIG. 10 and the like.

[0223] The candidate request destination display area 1226 is an area that displays candidates for the request destination lawyers.

[0224] The candidate request destination display area 1226 corresponds to step S1011 in FIG. 10 and the like. In the illustrated example, the candidate request destination display area 1226 receives an operation from the user to select a lawyer to request.

[0225] The condition specification reception unit 1228 is an operation member that receives specification of conditions for extracting candidate lawyers to whom a consultation is to be requested.

[0226] The condition specification reception unit 1228 corresponds to step S1011 in FIG. 10 and the like.

[0227] The request operation reception unit 1230 is an operation member that receives an operation to request advice from a lawyer.

[0228] The request operation reception unit 1230 corresponds to step S1011 in FIG. 10 and the like.

[0229] FIG. 16 is an example of an operation screen in which an expert receives a consultation request from a consulter and performs an operation.

[0230] The operation screen 1232 is a screen that displays the consultation content from the consulter to the user who is an expert and receives an operation in response to the request.

[0231] The account display area 1234 is an area that displays information on the account of the user who is an expert.

[0232] The request content display area 1236 is an area that displays the content of the consultation from the consulter.

[0233] The detailed display area 1238 is an area that displays the details of the consultation from the consulter.

[0234] As shown in the figure, the detailed display area 1238 displays the consultation from the consulter in a selectable manner for the expert. It corresponds to step S1023 in FIG. 10 and the like. In the detailed display area 1238, as shown in the figure, the server 20 refers to the chat consultation history database 212 and displays values obtained by scoring the consultation and the like.

[0235] The contact operation reception unit 1240 is an operation member that receives an operation to contact the consulter in response to a consultation request from the consulter.

[0236] The contact operation reception unit 1240 corresponds to step S1025 in FIG. 10 and the like.

[0237] The corresponding case display area 1242 is an area that displays the cases that the expert has received a request from the consulter and is handling (undertaking).

[0238] The detailed display area 1244 is an area for displaying details of cases that an expert is handling.

[0239] The search operation reception unit 1246 is an operation member that receives an operation to search for a requested case.

[0240] Figure 17 is an example of a screen for displaying a case record.

[0241] The operation screen 1300 is a screen that receives an operation for managing cases.

[0242] The account display area 1302 is an area for displaying information about a user's account.

[0243] In the illustrated example, the account display area 1302 displays information for identifying the logged-in user.

[0244] The new case registration area 1304 is an area that receives an operation for registering a new case.

[0245] The new case registration area 1304 receives the registration of data for each sub-field of the case management database 216 and updates the case management database 216.

[0246] The counselor designation unit 1306 is an operation member that receives the designation of information about a counselor related to a case.

[0247] When there is a master in which counselor information has already been registered, the counselor designation unit 1306 searches the master according to the input of the user's text or the like. In the example of Figure 18, counselor information is registered in the counselor designation unit 1306.

[0248] The interview data designation unit 1308 is an operation member that receives the designation of data during an interview between a counselor and an expert.

[0249] The interview data specifying unit 1308 accepts uploads of data such as voice data and recording data as data during the interview. Additionally, although not shown in the figure, it accepts registration of memos related to the case. In the example of FIG. 18, it shows that the upload of recording data has been accepted.

[0250] The case list display area 1310 is an area for displaying a list of cases.

[0251] The case list display area 1310 reads and displays records from the case management database 216 according to the user's viewing authority. Also, the server 20 accepts an operation to search for cases by the information of the counselor, etc., and displays the search results in the list display area 1312, etc. In the example of FIG. 18, it shows that a new record has been added to the case management database 216 due to accepting the registration of a new case in the new case registration area 1304. Also, in the example of FIG. 18, it shows that, by using the information registered in the record of the case after accepting the registration of a new case, a prompt is given to the server 95 of the large language model service, and the response result is registered in the record of the case.

[0252] The list display area 1312 is an area for displaying a list of case records.

[0253] The list display area 1312 accepts an operation from the user to specify each record, and displays detailed information of the specified record. In the example of FIG. 18, in the record of the newly registered case, the speech-to-text conversion of the voice data is displayed in the speech-to-text viewing operation unit 1314 (corresponding to step S1123 in FIG. 11). Also, in the example of FIG. 18, the summarization of the consultation content by the server 95 of the large language model service is displayed in the summary viewing operation unit 1316 (corresponding to steps S1125 and S1127 in FIG. 11).

[0254] FIG. 18 is an example of a screen showing the result of generating a summary of the consultation content based on the voice data of the consultation content in a case.

[0255] The speech-to-text viewing operation unit 1314 is an operation member that accepts an operation to view the speech-to-text data obtained by performing speech-to-text conversion on the consultation content.

[0256] The summary viewing operation unit 1316 is an operation member that accepts an operation to view the result of summarizing the consultation content.

[0257] The person correlation display area 1318 is an area that displays details of information about the persons related to the consultation content.

[0258] In the illustrated example, the person correlation display area 1318 displays the person names identified by the server 95 of the large language model service based on the consultation content. Also, in the illustrated example, the user is being asked about the relationship between the persons, and the answers are being received. This corresponds to step S1425 etc. in FIG. 14.

[0259] The extracted person display area 1320 is an area that displays the person names identified from the consultation content.

[0260] In the illustrated example, the extracted person display area 1320 displays that a plurality of persons have been identified.

[0261] The correlation specifying unit 1322 is an operation member that accepts the specification of an answer to a question asking about the relationship between persons.

[0262] In the illustrated example, the correlation specifying unit 1322 accepts an input of the relationship between the persons appearing from the user.

[0263] FIG. 19 is an example of an operation screen that accepts an operation to organize the consultation content.

[0264] The summary result display area 1324 is an area that displays the result of summarizing the consultation content.

[0265] In the example of FIG. 19, the summary result display area 1324 decomposes the result of summarizing the consultation content into, for example, sentence units and displays each as an object. In the example of FIG. 19, the user is prompted to perform an operation of rearranging the objects in chronological order, and it is displayed that a sentence is output in the rearranged order (corresponding to step S1221 in FIG. 12, etc.).

[0266] In the example of FIG. 20, the summary result display area 1324 supports the creation of sentences in the person correlation diagram.

[0267] The first object 1326 is the result of summarizing the consultation content.

[0268] The first object 1326 accepts an operation from the user to perform an operation of rearranging the positions with the second object 1328 and the third object 1330.

[0269] The second object 1328 is the result of summarizing the consultation content.

[0270] The third object 1330 is the result of summarizing the consultation content.

[0271] The generation operation unit 1332 is an operation member that accepts an operation of generating a sentence based on the objects with the specified order.

[0272] In the illustrated example, the generation operation unit 1332 accepts an operation from the user to cause the server 95 of the large language model service to generate a sentence that arranges the facts related to the consultation content in chronological order as if there were facts of the first object 1326, the second object 1328, and the third object 1330 in chronological order.

[0273] FIG. 20 is an example of an operation screen that accepts an operation of organizing the correlation of the characters appearing.

[0274] The correlation image specifying unit 1334 is an operation member that accepts the specification of the image to be uploaded.

[0275] The correlation image specifying unit 1334 accepts the upload of the image of the person correlation diagram (corresponding to steps S1311, S1323, etc. in FIG. 13). As shown in the figure, an explanatory text for explaining the method of creating the person correlation diagram may be displayed near the correlation image specifying unit 1334. For example, as described in the prompt explanation in step S1323 above, a text (for example, "The characters appearing are represented by figures such as rectangles or circles", "The names of the characters appearing are described in association with the figures", "The relationship between the characters is represented by an arrow and the text associated with the arrow") explaining the roles of figures, text, etc. used in the person correlation diagram is displayed near the correlation image specifying unit 1334 (in the illustrated example, the summary result display area 1324). Thereby, the user can easily create a person correlation diagram and can easily obtain the text indicating the correlation between the people.

[0276] In addition to uploading the image, the correlation image specifying unit 1334 may also accept the upload of a file of a presentation application or a file created by a document tool. For example, by acquiring these files and processing them as images, etc., a text indicating the correlation between people can be generated based on the figures, etc. included in these files.

[0277] The generation operation unit 1336 is an operation member that accepts an operation to cause the server 95 of the large language model service to generate a text of person correlation based on the image uploaded in the correlation image specifying unit 1334.

[0278] According to the user's operation, the generation operation unit 1336 causes the server 20 to send a prompt for generating a text indicating the correlation of the person for the image accepted for upload by the correlation image specifying unit 1334 to the server 95 of the large language model service. Thereby, the server 20 can acquire the text indicating the correlation of the person from the server 95 of the large language model service.

[0279] The correlation relationship display area 1338 is an area that displays a sentence indicating the correlation of a person, which is generated in response to an operation on the generation operation unit 1336.

[0280] The correlation relationship display area 1338 corresponds to steps S1327, S1313, etc. in FIG. 13.

[0281] <5 Operations (Second Embodiment)> The second embodiment will be described. After an expert hears the consultation content from the person seeking consultation, the consultation content is organized. When creating legal documents such as contracts, warning letters, pleadings, and pleadings, it is necessary to consider what claims to make. However, it is sometimes difficult to estimate how much the workload of the investigation for this purpose will be, which places a burden on the expert side. Also, the investigation work may be postponed. Therefore, in the second embodiment, an example in which the server 20 supports organizing arguments and conducting investigations corresponding to the arguments based on the consultation content will be mainly described. FIG. 21 is a diagram showing the flow of a process of identifying the arguments regarding the consultation content of the person seeking consultation by a large language model and associating and storing them with the record of the case.

[0282] In step S2121, the case management module 2048 of the server 20 gives a prompt for extracting the arguments corresponding to the consultation content to the server 95 of the large language model service based on the information of the consultation content associated with the record of the case in the case management database 216. As a result, the case management module 2048 obtains the information on the legal arguments regarding the consultation content from the server 95 of the large language model service and updates the case management database 216.

[0283] The case management module 2048 identifies the concerns of the counselor regarding the consultation content based on the information of the consultation content in the case management database 216. For example, the case management module 2048 provides a prompt to the server 95 of the large language model service to point out the concerns of the counselor regarding the consultation content. Thereby, the case management module 2048 may also obtain information on the legal arguments related to the consultation content by identifying the concerns of the counselor regarding the consultation content and providing a prompt to the server 95 of the large language model service to point out the arguments corresponding to the identified concerns.

[0284] In step S2123, the case management module 2048 of the server 20 searches a plurality of information sources related to law, such as a statute database (server 92 of the statute search service), a case database (server 91 of the case search service), a legal book database (server 93 of the book viewing service), and other information sources (server 94 of the information media service, server 97 of the SNS, the Internet, etc.) for the arguments related to the case record in the case management database 216 among the arguments obtained by the process of step S2121.

[0285] In step S2125, the case management module 2048 of the server 20 causes the server 95 of the large language model service to summarize the results of searching the plurality of information sources, and stores the summarized results in association with the case record related to the argument in the case management database 216.

[0286] For example, the case management module 2048 may search the server 91 of the case search service for the argument, and detect that the appellate court has amended the judgment of the lower court in the searched case. The case management module 2048 may also present the amendment content of the amended judgment of the appellate court related to the detection to the user.

[0287] In addition, the case management module 2048 searches for information stored in multiple information sources for the first information source that becomes past information in chronological order and the second information source that is future in chronological order than the first information source (for example, referring to the date when various data stored in the database was updated), and provides a prompt to the server 95 of the large language model service to point out the differences by comparing the results of searching the first information source and the results of searching the second information source, so that the differences are output to the server 95 of the large language model service and held in the case management database 216. The case management module 2048 may also present the output result of the differences to the user.

[0288] FIG. 22 is a diagram showing the flow of a process for generating a list of materials and evidence registered in a case record.

[0289] In step S2211, the terminal 10 receives an operation from the user to register materials and evidence related to the consultation content on the operation screen.

[0290] In step S2221, the case management module 2048 of the server 20 receives the registration of materials and evidence from the user and registers the information of the materials and evidence in the case record of the case management database 216. In the case management database 216, materials, evidence, preparatory documents, and other written data used in litigation procedures related to the consultation content of the case are managed in association with the case record.

[0291] In step S2223, the case management module 2048 of the server 20 transmits a prompt for listing these various data to the server 95 of the large language model service based on the data such as materials, evidence, and preparatory documents in the case management database 216. In this way, the case management module 2048 causes the large language model to generate information indicating a list of these based on various written data registered in the case management database 216.

[0292] In step S2225, the case management module 2048 of the server 20 acquires information indicating a list from the server 95 of the large language model service and registers it in the record of the case for the counselor in the case management database 216.

[0293] In step S2227, the case management module 2048 of the server 20 extracts the evidence described in the preparation document based on the data of the preparation document. The case management module 2048 identifies, for example, the locations (such as the words indicating the evidence) in the data of the preparation document that mention the evidence.

[0294] In step S2229, the case management module 2048 of the server 20 refers to the case management database 216 and outputs the list information and the result of extracting the evidence described in the preparation document to the terminal 10.

[0295] In step S2213, the terminal 10 displays the list information of materials, evidence, etc. and the extraction result of the evidence described in the preparation document.

[0296] <6 Screen example (Second embodiment)> FIG. 23 is an example of an operation screen for displaying information extracted by a large language model in the record of a case.

[0297] The case list display area 1340 is an area for displaying a list of cases.

[0298] The list display area 1342 is an area for displaying a list of case records.

[0299] In the example of FIG. 23, the argument display area 1342 displays, in the argument browsing operation unit 1344, the arguments identified by the server 95 of the large language model service (corresponding to step S2121 in FIG. 21). Also, in the example of FIG. 23, the research browsing operation unit 1346 displays the fact that the server 95 of the large language model service has searched for a plurality of information sources corresponding to the arguments and summarized the results (corresponding to steps S2123 and S2125 in FIG. 21).

[0300] The argument browsing operation unit 1344 is an operation member that accepts an operation to confirm the arguments identified by the server 95 of the large language model service.

[0301] The argument browsing operation unit 1344 displays the arguments corresponding to the consultation content according to the user's operation.

[0302] The research browsing operation unit 1346 is an operation member that accepts an operation to search for a plurality of information sources about an argument and confirm the summary of the search results.

[0303] In the illustrated example, the research browsing operation unit 1346 displays, as a result of searching for case law, an output indicating that the server 95 of the large language model service has changed the interpretation of the case law, and in response to that result, displays in the research browsing operation unit 1346 that the judgment has been corrected.

[0304] FIG. 24 is an example of an operation screen that displays a list of materials and evidence in the record of a case.

[0305] The evidence list display area 1348 is an area that displays a list of evidence associated with the record of the case specified by the user.

[0306] The evidence list display area 1348 corresponds to steps S2223, S2225, etc. in FIG. 22.

[0307] The evidence acquisition unit 1350 is an operation member that accepts an operation to acquire evidence information in association with a case.

[0308] The evidence acquisition unit 1350 accepts registration of various data serving as evidence, such as documents, images, and voices, corresponding to steps S2211 and S2221 in FIG. 22.

[0309] The list display area 1352 is an area for displaying a list of evidence associated with a case.

[0310] The list display area 1352 corresponds to steps S2229 and S2213 in FIG. 22.

[0311] The description confirmation operation unit 1354 is an operation member that accepts an operation for confirming a list of evidence described in written data such as preparatory documents associated with a case.

[0312] The description confirmation operation unit 1354 corresponds to steps S2229 and S2213 in FIG. 22. The server 20, for example, while detecting a description specifying evidence in written data such as preparatory documents, outputs a list of the detected evidence in a list format or the like.

[0313] <7 Operations (Third Embodiment)> The third embodiment will be described. After an expert hears the consultation content from the consulter, organizes the consultation content, clarifies the legal points, and constructs claims corresponding to the points, legal documents such as a complaint and an answer are created. Therefore, in the third embodiment, a technique for the server 20 to support the creation of such legal documents as a complaint, an answer, and also documents such as a contract and a term sheet will be described. FIG. 25 is a diagram showing the flow of a process for generating written data related to law based on the information of a case record.

[0314] In step S2511, the terminal 10 accepts an operation from the user to generate a deliverable related to law. Examples of deliverables related to law include the following. · Those that define the content of agreement between parties, such as a contract and a term sheet · Those that make legal claims between parties, such as warning letters and response letters · Those related to legal procedures such as litigation or trial, such as pleadings, answers, and preparatory written documents In step S2521, the case management module 2048 of the server 20 extracts information to be included in the work product from the consultation content information associated with the case record in the case management database 216.

[0315] In step S2523, the case management module 2048 of the server 20 uses the extracted information to generate a prompt for causing the work product to be output by the large language model, and transmits the generated prompt to the server 95 of the large language model service.

[0316] In step S2525, the case management module 2048 of the server 20 obtains the result of generating the work product from the server 95 of the large language model service and registers it in the case record of the client in the case management database 216.

[0317] Here, in the case management database 216, at least one of the information of the parties involved in the consultation content or the information of the agents in the legal procedure is managed as the case record. In step S2521, the case management module 2048 may extract at least one of these managed party information or agent information. In step S2523, the case management module 2048 may use at least one of the extracted party information or agent information to generate a prompt for outputting at least one of the first document data submitted in the litigation procedure, the second document data for notifying the parties of the legal claims of the parties, and the third document data regarding the contract conditions agreed upon between the parties as the work product. In step S2525, the case management module 2048 receives at least one of the first document data, the second document data, and the third document data as a response output by the server 95 of the large language model service and registers it in the case record of the case management database 216.

[0318] In addition, when the case management module 2048 outputs the first document data in step S2523, it may generate a prompt to output at least one of a complaint, an answer, and a pretrial brief. When outputting the third document data, it may generate a prompt to output at least one of a contract and a term sheet defining contract terms.

[0319] Here, for a complaint, an answer, and a pretrial brief, the standard writing methods (such as the format as a document and headings) are provided in books (which may be books provided by the server 93 of the book browsing service) and websites. The case management module 2048 generates a prompt including an instruction to generate a deliverable by applying the information related to the consultation content while referring to these standard writing methods and the data of sample documents, and provides it to the server 95 of the large language model service, so that the server 95 of the large language model service generates the deliverable.

[0320] For example, the case management module 2048 may provide the following prompt to the server 95 of the large language model service, so that the server 95 of the large language model service outputs a written response such as a rebuttal. · There are books (such as those made available for users to view on the server 93 of the book browsing service) and articles on the web that contain examples of written rebuttals for making legal claims. Include in the prompt an instruction to create a written document that reflects the claim content information stored in the case management database 216 by referring to these examples, such as examples of rebuttals along the lines of the material facts. · Include in the prompt an instruction to create a written document in accordance with the guidelines shown in the above-described standard writing methods for written rebuttals (such as separating the description of "denial" and "defense"). In addition, in order to suggest evidence to be presented to supplement the claim along with the counterargument, the case management module 2048 may also provide the following prompts to the server 95 of the large language model service. · Include in the prompt an instruction to enumerate the evidence presented in past cases (records of each case stored in the case management database 216, precedents stored in a case law database, etc., explanations of precedents published as articles or books, etc.) for the defenses asserted in the counterargument. · Include in the prompt an instruction to enumerate the evidence presented in past cases when denying in the counterargument. This enables the user to more easily understand, for example, the degree of evidence for which the defense was recognized, and makes it even easier to create the written counterargument.

[0321] Also, in the case management database 216, information on the term sheet that defines the contract terms is managed as a record of the case. The case management module 2048 may generate a prompt to output a contract as the third document data using the information on the term sheet of the case record in step S2523. The case management module 2048 receives the contract document data as the output response from the server 95 of the large language model service.

[0322] Here, for the term sheet and the contract, the standard writing methods (document formats, headings, etc.) are provided in books (which may be books provided by the server 93 of the book viewing service), websites, etc. The case management module 2048 generates a prompt including an instruction to generate the work product by applying the information (such as contract terms) related to the consultation content while referring to these standard writing methods and the data of the sample documents, and provides it to the server 95 of the large language model service, so that the server 95 of the large language model service generates the work product.

[0323] Also, in step S2523, the case management module 2048 may generate a prompt that includes causing the definition of the contract to be created by referring to a thesaurus or dictionary database that stores the definitions of terms. As a result, a contract with unified terms can be output by the server 95 of the large language model service.

[0324] The case management module 2048 stores the response received from the server 95 of the large language model service in association with the record of the case from which the information related to the generation of the prompt has been extracted in the case management database 216.

[0325] In step S2527, the server 20 outputs the deliverable information of the case record in the case management database 216 to the terminal 10.

[0326] In step S2513, the terminal 10 displays the generated deliverable information.

[0327] FIG. 26 is a diagram showing the flow of a process for generating a counterargument assumed for an argument.

[0328] In step S2611, the terminal 10 receives from the user an operation to generate a counterargument assumed for the argument regarding the argument information stored in association with the case in the case management database 216.

[0329] In step S2621, the case management module 2048 of the server 20 generates a prompt for outputting to the large language model a counterargument against the claim content between the parties in the document data held in the case management database 216.

[0330] Specifically, in the case management database 216, as records of cases, it manages information of written data that describes the content of claims asserted by parties for each argument regarding the consultation content. The case management module 2048 generates a prompt for outputting a counterargument to the content of claims between parties in the written data to a large language model.

[0331] In step S2623, the case management module 2048 of the server 20 transmits the generated prompt to the server 95 of the large language model service. In this way, by providing the generated prompt to the large language model, the case management module 2048 causes the server 95 of the large language model service to output a counterargument.

[0332] In step S2625, the case management module 2048 of the server 20 acquires the information of the output counterargument from the server 95 of the large language model service and registers it in the case record regarding the counselor in the case management database 216.

[0333] In step S2621, the case management module 2048 may also generate a prompt for searching for a counterargument with the content of claims in the written data of each case (including other cases different from the case for which a counterargument is output) accumulated in the case management database 216 or the data of published judgment documents as search targets and having the large language model summarize the search results. In step S2623, the case management module 2048 may output the summarized counterargument to the server 95 of the large language model service by providing the generated prompt to the large language model.

[0334] For example, in the case of a traffic accident or a claim for the return of an overpayment, depending on the type of claim in the case (classified according to the basis clause), in past cases, the content of the parties' assertions regarding the argument is identified from the judgment text and each case managed in the case management database 216, and a prompt for summarizing the content of the identified counterarguments is given to the server 95 of the large language model service, etc., so that the content of the counterarguments assumed from the other party regarding the argument can be generated by the server 95 of the large language model service.

[0335] In step S2627, the case management module 2048 of the server 20 outputs the counterargument information of the case record in the case management database 216 to the terminal 10.

[0336] Thereby, the case management module 2048 presents the counterargument output by the server 95 of the large language model service to the user.

[0337] In step S2613, the terminal 10 displays the generated counterargument information.

[0338] FIG. 27 is a diagram showing the flow of a process for assisting in the interpretation of a contract.

[0339] In step S2711, the terminal 10 receives from the user an operation of designating a contract in the case record.

[0340] In step S2721, the case management module 2048 of the server 20 generates a prompt for illustrating the citation relationship of each clause of the contract data designated by the user. The prompt includes information for designating the contract data (for example, a link to the contract data or the full text of the contract data).

[0341] In step S2723, the case management module 2048 of the server 20 transmits the generated prompt to the server 95 of the large language model service.

[0342] In step S2725, the case management module 2048 of the server 20 acquires the illustrated information on the citation relationship of each clause output from the server 95 of the large language model service, and registers it in the record of the case regarding the counselor in the case management database 216.

[0343] In step S2727, the case management module 2048 of the server 20 outputs the illustrated information on the citation relationship of each clause of the case record to the terminal 10.

[0344] In step S2713, the terminal 10 displays the illustrated information on the citation relationship of each generated clause.

[0345] <8 Screen Example (Third Embodiment)> FIG. 28 is an example of an operation screen for generating written data related to law.

[0346] The generation support unit 1356 is an area for receiving an operation to support the generation of work products.

[0347] The registration information specifying unit 1358 is an operation member for receiving the specification of case information to be included in the work product to be generated.

[0348] In the illustrated example, the registration information specifying unit 1358 is specified to include, in the work product, information on the parties, the content of the claims regarding the arguments, etc. among the case information. This corresponds to steps S2511, S2521, etc. in FIG. 25.

[0349] The work product specifying unit 1360 is an operation member for receiving the specification of the type of work product to be generated by the server 95 of the large language model service.

[0350] The work product specifying unit 1360 receives the following specifications from the user as the type of work product. · First document data to be submitted in litigation procedures (e.g., complaint, answer, preparatory document) · Second document data for notifying the legal claims of the parties to each other (e.g., warning letter, response letter) · A third document data which is a document regarding the contract conditions agreed upon between the parties (for example, a contract, a term sheet defining the contract conditions) The dictionary specifying unit 1362 is an operation member that receives the specification of a dictionary to be referred to by the server 95 of the large language model service when generating a work product.

[0351] The generation operation unit 1364 is an operation member that receives an operation to generate a work product by the server 95 of the large language model service based on the specified conditions.

[0352] The generation operation unit 1364 corresponds to step S2511 in FIG. 25 and the like.

[0353] The browsing operation unit 1366 is an operation member that receives an operation to browse a work product generated by the server 95 of the large language model service.

[0354] FIG. 29 is an example of an operation screen that displays counterarguments assumed for an argument.

[0355] The counterargument generation unit 1368 is an area that receives an operation to generate counterarguments assumed from the other party for an argument.

[0356] The generation operation unit 1370 is an operation member that receives an operation to generate a counterargument by the server 95 of the large language model service for the content of the claim registered in the record of the case.

[0357] The generation operation unit 1370 corresponds to step S2611 in FIG. 26 and the like.

[0358] The generation result display area 1372 is an area that displays the counterargument generated by the server 95 of the large language model service.

[0359] The generation result display area 1372 corresponds to steps S2627, S2613 in FIG. 26 and the like.

[0360] The case viewing operation unit 1374 is an operation member that accepts an operation to view other cases used as information sources when the server 95 of the large language model service generates a counterargument.

[0361] The case viewing operation unit 1374 may, for example, display links to other cases managed in the case management database 216, information on the claim contents (including the opponent's claim contents) included in the document data registered in other cases.

[0362] The precedent viewing operation unit 1376 is an operation member that accepts an operation to view precedents used as information sources when the server 95 of the large language model service generates a counterargument.

[0363] The precedent viewing operation unit 1376 may, for example, display excerpts of precedents accumulated in the server 91 of the precedent search service, links to precedents, links to court precedents, excerpts of books referring to precedents in the server 93 of the book viewing service, links to the books, etc.

[0364] Figure 30 is an example of an operation screen for assisting in the interpretation of a contract.

[0365] The contract business support unit 1378 is an area that accepts an operation to support the operation of referring to and creating a contract based on the data stored in the case management database 216.

[0366] The generation operation unit 1380 is an operation member that accepts an operation to cause the server 95 of the large language model service to generate a contract based on the data registered in the specified case.

[0367] In the illustrated example, the generation operation unit 1380 accepts an operation to arrange the description of the contract data registered in the case. This corresponds to step S2711 in Figure 27.

[0368] The generation result display area 1382 is an area that displays the contract generated by the server 95 of the large language model service.

[0369] The server display area 1384 of the information media service is an area for displaying the result output by the server 95 of the large language model service regarding the citation relationship of the contract document.

[0370] In the illustrated example, when there is a citation relationship between clauses, the server display area 1384 of the information media service displays the source clause and the cited clause side by side as a list. This corresponds to steps S2727, S2713, etc. in FIG. 27.

[0371] The dictionary specification unit 1386 is an operation member that accepts a dictionary specification defining the language used in the contract document.

[0372] The template registration operation unit 1388 is an operation member that accepts an operation to register the generated contract document as a template.

[0373] As shown in the illustrated example, the template registration operation unit 1388 displays that it accepts registration as a template in clause units. In this way, using the newly registered or updated template, the server 20 causes the server 95 of the large language model service to generate a contract document according to the user's operation. For example, the server 20 may generate a prompt for creating a contract document according to specified conditions while referring to the templates of the accumulated contract documents, and obtain the generated contract document by transmitting the prompt to the server 95 of the large language model service. Also, the server 20 may make the registered contract document templates searchable and provide the templates to the user.

[0374] <Modification Example> It may be possible to combine each of the above embodiments. Also, in addition to the aspects described in the above embodiments, the following may be done.

[0375] (1) Improvement in the reliability of the generated answer In the description of the above embodiment, when the answer generated by the server 95 of the large language model service includes the case number, legal provision, source of the guideline, etc. as the basis, whether these generated answers are actual existing cases, laws, guidelines, etc., it may also be collated by searching the databases of the server 91 of the case search service, the server 92 of the legal search service, the server 93 of the book browsing service, the server 94 of the information media service, etc. Specifically, the server 20 determines whether the introduction of the content shown in the case and the case number are included in the answer generated by the server 95 of the large language model service. For example, the case number is assigned according to a predetermined rule (such as "No. XXXXX of (XX) in Heisei XX year"), and the description conforming to these rules is extracted as the case number. The server 20 inquires the server 91 of the case search service, etc. based on the case number, obtains the judgment text, abstract, etc. of the precedent, and determines whether it is similar or identical to the result generated by the server 95 of the large language model service. For example, the server 20 may determine similarity based on the degree of word matching included in the text, or may vectorize the meaning of the document and determine similarity based on the vector distance.

[0376] If the server 20 determines that they are not similar, it may cause the server 95 of the large language model service to generate an answer again, or may respond to the user with the case number of the actually existing case as a result of inquiring the server 91 of the case search service, etc. For example, for the introduction text of the case included in the answer generated by the server 95 of the large language model service, a similar judgment text may be searched from the server 91 of the case search service, etc., and the case number of the corresponding precedent may be responded.

[0377] Thereby, when the answer generated by the server 95 of the large language model service includes a non-existing case, etc., it is possible to determine whether the generated answer is appropriate by referring to the original case, etc.

[0378] In addition, when the server 20 checks whether the content of the answer generated by the server 95 of the large language model service is described in the references such as case numbers, legal provisions, guideline sources, and references as the basis in the answer generated by the server 95 of the large language model service, it may also be executed by giving a prompt to the server 95 of the large language model service to perform such verification. The server 20 can evaluate the reliability of the answer generated by the server 95 of the large language model service upon receiving the verification result, and may also present the evaluation result to the user.

[0379] For example, while presenting the generated answer and the basis to the user, the server 20 may also present to the user whether there is a description in the basis as a result of the verification of the basis.

[0380] In addition, for example, if the server 20 causes the server 95 of the large language model service to perform such verification and the server 95 of the large language model service outputs that there is no description in the basis, the server 20 may not present the answer generated by the server 95 of the large language model service to the user and may notify the user such as "Failed to generate an answer".

[0381] (2) Designate domestic and overseas information as information sources The server 20 may receive from the user a designation of whether the information is issued domestically or overseas (or in a specific country), and receive an instruction to generate an answer by the server 95 of the large language model service with reference to the information source according to the user's designation (for example, when the user designates Europe, define in the prompt to summarize the results of searching for European information).

[0382] Thereby, in addition to legal arrangement, information about overseas cases can also be provided to the user.

[0383] (3) Classify questions to generate answers for the large language model service and create prompts according to the classified results In addition to what has been described in the above embodiments, in order to cause the large language model service to generate the answer intended by the user, the user's question may be classified, a prompt may be created according to the classified result, and the created prompt may be provided to the server 95 of the large language model service.

[0384] For example, in advance, the server 20 holds a classification list for classifying questions, and for each classification, criteria for causing the large language model service to generate an answer are prepared.

[0385] When the server 20 receives an input of a question from the user, it determines which classification in the question list the input question belongs to. For example, the server 20 uses the user's question as an input and provides a prompt to the effect of "answering which classification in the classification list the input question corresponds to" to the server 95 of the large language model service. Thereby, the server 95 of the large language model service generates an answer as to which classification in the classification list the user's question corresponds to. When the server 20 receives the answer generated by the server 95 of the large language model service, it refers to the classification list, generates a prompt including the "criteria for generating an answer" associated with the corresponding classification, and provides the generated prompt to the server 95 of the large language model service. Thereby, the server 20 can obtain the answer generated by the server 95 of the large language model service for the question received from the user based on the "criteria for generating an answer" shown in the classification list.

[0386] For example, by classifying the user's question, the server 20 may select information resources such as books and case laws as the "criteria for generating an answer".

[0387] For example, when it can be determined from the user's question that the user wants to know about a procedure, it may not be necessary to include case information in the answer to the user. Therefore, in this case, the server 20 creates a prompt with the criterion of "not including cases" for "generating an answer". For example, when the user enters a question such as "Please tell me about the precautions for divorce by mutual consent", it may be desired to provide an answer about the procedure.

[0388] Also, when it can be determined from the user's question that the user wants to know about a case or the definition of a term, it may be possible to generate an answer targeting cases as the "criterion for generating an answer".

[0389] In this way, instead of transmitting all information at once to the server 95 of the large language model service to generate an answer, by giving a prompt for the classification to which the question belongs, it may be possible to suppress the consumption of computing resources of the server 95 of the large language model service.

[0390] (4) Reinvestigation by an expert's instruction when the server 95 of the large language model service conducts argumentation and research based on the information in the case record In the above embodiment, with reference to FIGS. 21 to 25, it has been described that by registering the data of the consultation content in the case record, the server 95 of the large language model service extracts legal arguments, conducts a search corresponding to the arguments, and registers the results in the case record.

[0391] The server 20 may present the arguments extracted by the server 95 of these large language model services and a summary of the search results corresponding to the arguments to the user who is an expert, accept an operation for the expert to confirm these, and register them in the case management database 216. At this time, the server 20 may also accept an instruction from an expert such as a lawyer to redo the extraction of the arguments and the investigation by the search corresponding to the arguments, re-perform the above-mentioned extraction of the arguments, etc., and present the results to the user.

[0392] Regarding the results of legal interpretation, compare with the search results in information sources different from legal-related ones such as legal books and case laws. Server 20 may also present to the user, over time, the legal interpretations shown in legal-related books and case laws in a comparable manner to the values of people in the world.

[0393] For example, Server 20 searches the servers 94 of information media services and the servers 96 of SNSs for legal arguments. For example, if searching SNSs, etc. for recent past case laws, the reactions of SNS users can be obtained as search results. Server 20 may also contrast the interpretation of past case laws with the results summarized by Server 95 of the large language model service from the search of the reactions of users in SNSs, etc., and present them to the user. Thereby, it is possible to suggest the possibility of changes in future case laws, legal amendments, and changes in academic theories.

[0394] (6) Assistance in reading judgment documents In the above embodiment, an example of searching for legal arguments and corresponding case laws, etc. was explained.

[0395] Here, when there is a judgment document of a higher court that modifies and indicates the original judgment, Server 20 may also read and display the description of the original judgment based on the content modified by the judgment document of the higher court. Thereby, for example, by partially modifying the original judgment, the high court judgment can be made easier to read.

[0396] (7) Creation of a report on the investigation results regarding legal arguments Server 20 may also cause Server 95 of the large language model service to generate a report in accordance with a predetermined format such as documents and the text of emails, etc., in order to facilitate experts reporting the investigation results based on legal arguments regarding a case to the person consulting.

[0397] (8) Generate a contract while maintaining the indent setting of the contract The server 20 may also set indents in the contract data so that articles, clauses, and items can be identified separately (such as making the amount of indent different for articles, clauses, and items), and generate a contract based on the information of the project record.

[0398] As described above, some embodiments of the present disclosure have been described. However, these embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the gist of the invention. These embodiments and their modifications are to be included in the scope and gist of the invention, as well as in the invention described in the claims and the equivalent scope thereof.

[0399] The functions realized by the components described in this specification may be implemented in circuitry or processing circuitry including a general-purpose processor, a specific-purpose processor, an integrated circuit, ASICs (Application Specific Integrated Circuits), a CPU (a Central Processing Unit), a conventional circuit, and / or a combination thereof, which are programmed to realize the described functions. The processor includes transistors and other circuits and is regarded as circuitry or processing circuitry. The processor may be a programmed processor that executes a program stored in a memory.

[0400] In this specification, circuitry, unit, and means are hardware programmed to realize the described functions or hardware that executes them. The hardware may be any hardware disclosed in this specification or any hardware known to be programmed or execute to realize the described functions.

[0401] When the hardware is a processor regarded as being of the circuitry type, the circuitry, means, or unit is a combination of hardware and software used to configure the hardware and / or the processor.

[0402] <Supplementary Note> The matters described in the above embodiments are appended below.

[0403] <Supplementary Note of the First Embodiment>

[0404] (Supplementary Note 1) A program for operating a computer equipped with a computer processor, the program causing the computer processor to execute steps of: receiving input of consultation data indicating the content of a consultation from a consulter; obtaining a summarized result of the consultation content by giving a prompt to a large language model to summarize the consultation content shown in the consultation data along predetermined items; and associating the consultation content summarized along the predetermined items with the consulter and storing it in a storage unit so that an expert responding to the consultation from the consulter can refer to it.

[0405] (Supplementary Note 2) The program according to Supplementary Note 1, wherein in the receiving step, voice data indicating the consultation content is received as the consultation data, speech-to-text data obtained by speech-to-text conversion of the voice data is acquired, and in the step of storing it in the storage unit, the speech-to-text data is stored in association with the consulter, and at least any one of information on the result of determining the speaker, information on the result of determining the emotion, and information on the timing when there was a consultation from the consulter in the speech-to-text data is further stored in the storage unit.

[0406] (Supplementary Note 3) The program according to any one of Supplementary Notes 1 to 2, wherein in the obtaining step, a prompt for sorting and organizing the consultation content included in the consultation data in chronological order is given as the prompt to obtain a summarized result, and in the step of storing it in the storage unit, the summarized result sorted and organized in chronological order is stored in association with the consulter.

[0407] (Appendix 4) Based on the result of sorting and summarizing the consultation content by time series using a large language model, each of the sorted results is displayed on the screen as an object, and the user is accepted to perform an operation of rearranging the objects. By giving a large language model a prompt to generate a text in time series based on the order of rearrangement in response to the operation of rearranging the objects, the program according to Appendix 3 further obtains the summarized result sorted by time series.

[0408] (Appendix 5) In the storage unit, each consultation from the consulter is managed as a case including a case and predetermined management items. In the step of storing in the storage unit, each item of the consultation content summarized along the predetermined items is associated with each management item managed as a case in the storage unit and stored. The program according to any one of Appendices 1 to 4.

[0409] (Appendix 6) In the storage unit, as predetermined management items, at least any one of the consultation content from the consulter, the next action to be taken, and the concerns of the consulter is included and managed as a case. In the step of obtaining, by giving a large language model a prompt to summarize at least any one included in the predetermined management items as a predetermined item, the summarized result is obtained. The program according to Appendix 5.

[0410] (Appendix 7) In the receiving step, as consultation data, voice data indicating the consultation content is received, the speech-to-text data obtained by speech recognition of the voice data is obtained, and in the step of storing in the storage unit, the speech-to-text data is associated with the consulter and stored, and information on the result of determining the emotion of the consulter is further stored in the storage unit. In the step of obtaining, based on the voice data of the consultation content of the consulter and the information on the result of determining the emotion, the concerns of the consulter are extracted, and in the step of storing in the storage unit, the information on the concerns of the consulter is stored as case information. The program according to Appendix 6.

[0411] (Appendix 8) The program causes a computer processor to further execute a step of receiving input of image data showing a correlation diagram of persons related to the consultation content from the person seeking consultation, a step of analyzing the image data and obtaining a sentence showing the correlation of persons by giving a prompt to a large language model to generate a sentence showing the correlation of persons, and a step of outputting the obtained sentence showing the correlation of persons. The program according to any one of Appendices 1 to 7.

[0412] (Appendix 9) In the receiving step, as consultation data, voice data showing the consultation content is received, and in the step of obtaining the speech-to-text data obtained by speech-to-text conversion of the voice data and storing it in the storage unit, the speech-to-text data is stored in association with the person seeking consultation, and in the speech-to-text data, a step of identifying a word indicating a person, and when a word indicating a person is identified, a step of presenting a question asking about the relationship between the identified person and other persons appearing in the consultation content to the person seeking consultation or an expert and receiving an input of an answer, and a step of storing the received answer in the storage unit are further executed. Program.

[0413] (Appendix 10) A method executed by a computer equipped with a computer processor, the method comprising a step in which the computer processor receives input of consultation data showing the consultation content from the person seeking consultation, and a step in which the computer processor obtains a result of summarizing the consultation content by giving a prompt to a large language model to summarize the consultation content shown in the consultation data along a predetermined item, and a step of storing the consultation content summarized along the predetermined item and the person seeking consultation in association with each other in a storage unit so that an expert responding to the consultation from the person seeking consultation can refer to it. Method.

[0414] (Supplementary Note 11) An information processing apparatus, wherein a control unit of the information processing apparatus executes: a step of receiving an input of consultation data indicating consultation content from a consulter; a step of obtaining a result of summarizing the consultation content by giving a prompt to a large language model so as to summarize the consultation content indicated in the consultation data along a predetermined item; and a step of associating the consultation content summarized along the predetermined item with the consulter and storing the same in a storage unit so that an expert responding to the consultation from the consulter can refer to it.

[0415] <Supplementary Note of the Second Embodiment>

[0416] (Supplementary Note 1) A program for operating a computer including a processor, wherein in a storage unit, each of the consultation contents from a consulter is configured to be managed as a record of a case, and the program causes the processor to execute: a step of receiving registration of the consultation content of the consulter and storing the same in the storage unit in association with the record of the case; a step of obtaining information on an argument by giving a prompt for extracting an argument corresponding to the consultation content to a large language model based on the information on the consultation content associated with the record of the case; and a step of storing the obtained information on the argument in the storage unit in association with the record of the case related to the consultation content.

[0417] (Supplementary Note 2) The program according to Supplementary Note 1, wherein in the obtaining step, based on the information on the consultation content, a concern point that the consulter regarding the consultation content is concerned about is specified, and an argument corresponding to the specified concern point is obtained by a large language model.

[0418] (Supplementary Note 3) The program causes the processor to further execute the steps of: searching a plurality of information sources related to laws, such as a statute database, a case law database, a legal book database, etc., for the arguments stored in the storage unit in association with the records of the cases; summarizing the results of searching the plurality of information sources by a large language model; and storing the summarized results in the storage unit in association with the records of the cases related to the arguments. The program is as described in any one of Appendices 1 to 2.

[0419] (Appendix 4) In the searching step, search the case law database, detect in the searched cases that the appellate court has amended the judgment of the lower court, and present the amendment content of the judgment amended by the appellate court related to the detection to the user. The program is as described in Appendix 3.

[0420] (Appendix 5) In the searching step, for the information stored in a plurality of information sources, search a first information source that is past information in chronological order and a second information source that is future in chronological order compared to the first information source, compare the results of searching the first information source with the results of searching the second information source, output the different content to a large language model, and present the output result of the different content to the user. The program is as described in Appendix 3.

[0421] (Appendix 6) In the storage unit, manage materials, evidence, preparatory documents, and other written data used in litigation procedures related to the consultation content of the case in association with the records of the case, and generate information indicating a list of these based on various written data registered in the storage unit by a large language model. The program is as described in any one of Appendices 1 to 5.

[0422] (Appendix 7) In the storage unit, in association with the record of the case, it manages materials, evidence, preparatory documents related to the consultation content of the case, and other written data used in litigation procedures. Based on the data of the preparatory documents registered in the storage unit, it extracts the evidence described in the preparatory documents and presents the extracted result to the user. The program described in Supplementary Note 6.

[0423] (Supplementary Note 8) A method executed by a computer comprising a processor and a storage unit, The storage unit is configured to manage each consultation content from the consulter as a record of the case. The method includes steps where the processor receives the registration of the consultation content from the consulter and stores it in the storage unit in association with the record of the case; gives a prompt for extracting the points corresponding to the consultation content to a large language model based on the information of the consultation content associated with the record of the case, thereby obtaining the information of the points; and stores the obtained information of the points in the storage unit in association with the record of the case related to the consultation content.

[0424] (Supplementary Note 9) An information processing apparatus comprising a storage unit, where the storage unit is configured to manage each consultation content from the consulter as a record of the case. The control unit of the information processing apparatus receives the registration of the consultation content from the consulter and stores it in the storage unit in association with the record of the case; gives a prompt for extracting the points corresponding to the consultation content to a large language model based on the information of the consultation content associated with the record of the case, thereby obtaining the information of the points; and stores the obtained information of the points in the storage unit in association with the record of the case related to the consultation content.

[0425] (Supplementary Note of the Third Embodiment)

[0426] (Supplementary Note 1) A program for operating a computer equipped with a processor, configured to manage each consultation content from a consulter as a record of a case in a storage unit, the program causes the processor to: extract information to be included in the work product from the information of the consultation content associated with the record of the case; generate a prompt for outputting the work product by a large language model using the extracted information; provide the generated prompt to the large language model and receive a response from the large language model; and present the work product as the received response to the user.

[0427] (Appendix 2) In the storage unit, at least one of the information of the parties involved in the consultation content or the information of the agent in the legal procedure is managed as a record of the case. In the extraction step, at least one of the information of the parties or the information of the agent is extracted. In the generation step, at least one of the extracted information of the parties or the agent is used to generate a prompt for outputting at least one of the first document data to be submitted in the litigation procedure, the second document data for notifying the legal claims of the parties to each other, and the third document data which is a document regarding the contract conditions agreed between the parties as the work product, and in the receiving step, at least one of the first document data, the second document data, and the third document data is received as the output response. The program according to Appendix 1.

[0428] (Appendix 3) In the generation step, when outputting the first document data, generate a prompt for outputting at least one of a complaint, an answer, and a pretrial brief. When outputting the third document data, generate a prompt for outputting at least one of a contract and a term sheet defining the contract conditions. The program according to Appendix 2.

[0429] (Appendix 4) In the storage unit, as a record of a case, information on a term sheet that defines contract terms is managed. In the generating step, a prompt is generated to output a contract as third document data using the information on the term sheet. In the receiving step, contract document data as the output response is received. A program according to any one of Appendices 2 to 3.

[0430] (Appendix 5) A program according to Appendix 4, wherein in the generating step, a prompt is generated that includes causing a dictionary or dictionary database that records definitions of terms to be referred to create a definition of a contract.

[0431] (Appendix 6) In the storage unit, as a record of a case, information on written data that describes the content of claims made by parties for each point of argument regarding the consultation content is managed. The program further causes the processor to generate a prompt for outputting to a large language model a counterargument against the content of claims between parties in the written data, gives the generated prompt to the large language model to cause the large language model to output a counterargument, and presents the output counterargument to the user. A program according to any one of Appendices 1 to 5.

[0432] (Appendix 7) Based on the content of claims between parties in the written data, a prompt is generated to search for a counterargument by using as search targets the content of claims in the written data of each case stored in the storage unit or data of publicly disclosed judgment documents, and cause the large language model to summarize the search results. By giving the generated prompt to the large language model, a summarized counterargument is output by the large language model. A program according to Appendix 6.

[0433] (Appendix 8) In the storage unit, the data of the contract is managed in association with the record of the case. In the generating step, a prompt for illustrating the citation relationship of each clause of the contract data is generated. In the receiving step, the illustrated information is received by providing the prompt to a large language model. A program according to any one of Appendices 1 to 7.

[0434] (Appendix 9) The response from the large language model received in the receiving step is stored in the storage unit in association with the record of the case from which the information related to the generation of the prompt has been extracted. A program according to any one of Appendices 1 to 8.

[0435] (Appendix 10) A method for operating a computer equipped with a processor, wherein in the storage unit, each consultation content from the consulter is configured to be managed as a record of the case. The method includes steps: the processor extracts information to be included in the work product from the information of the consultation content associated with the record of the case; uses the extracted information to generate a prompt for outputting the work product by a large language model; provides the generated prompt to the large language model and receives a response from the large language model; and presents the work product as the received response to the user.

[0436] (Appendix 11) An information processing apparatus, wherein in the storage unit, each consultation content from the consulter is configured to be managed as a record of the case. The control unit of the information processing apparatus extracts information to be included in the work product from the information of the consultation content associated with the record of the case; uses the extracted information to generate a prompt for outputting the work product by a large language model; provides the generated prompt to the large language model and receives a response from the large language model; and presents the work product as the received response to the user.

Claims

1. A program for operating a computer comprising a processor, configured to manage each of the consultation contents from a consulter as a record of a case in a storage unit, the program causes the processor to extract information to be included in the work product from the information of the consultation content associated with the record of the case; generate a prompt for causing the work product to be output by a large language model using the extracted information; give the generated prompt to the large language model and receive a response from the large language model; present the work product as the received response to the user, and execute, in the storage unit, manage at least one of information of a party related to the consultation content or information of an agent in a legal procedure as the record of the case, in the extracting step, extract at least one of the information of the party or the information of the agent, in the generating step, use at least one of the extracted information of the party or the information of the agent to generate the prompt for outputting at least one of first document data to be submitted in a litigation procedure, second document data for notifying a legal claim of a party among the parties, and third document data which is a document regarding contract conditions agreed among the parties as the work product; in the receiving step, receive at least one of the first document data, the second document data, and the third document data as the output response, in the storage unit, manage information of a term sheet defining contract conditions as the record of the case, in the generating step, generate the prompt for outputting a contract as the third document data using the information of the term sheet, in the receiving step, receive the contract data as the output response. A program.

2. The program according to claim 1, wherein in the generating step, the prompt is generated including creating a definition of the contract by referring to a dictionary or a dictionary database recording definitions of terms.

3. In the generating step, When outputting the first document data, generate a prompt for outputting at least one of a complaint, an answer, and a pretrial brief. The program according to claim 1, wherein when outputting the third document data, a prompt for outputting at least one of a contract and a term sheet defining contract terms is generated.

4. A program for operating a computer including a processor, In a storage unit, each piece of consultation content from a consultant is configured to be managed as a record of a case, The program causes the processor to extract information to be included in the work product from the information of the consultation content associated with the record of the case; generate a prompt for outputting the work product by a large language model using the extracted information; give the generated prompt to the large language model and receive a response from the large language model; present the work product as the received response to the user, and execute, In the storage unit, as the record of the case, information of written data describing the content of the claim asserted for each point of contention between the parties regarding the consultation content is managed, The program further causes the processor to generate a prompt for outputting a counterargument against the content of the claim between the parties in the written data to the large language model, give the generated prompt to the large language model to cause the large language model to output the counterargument, A program for presenting the output counterargument to the user.

5. Based on the content of the claim between the parties in the written data, search for a counterargument with the content of the written data of each case stored in the storage unit or the data of a published judgment as a search target, and generate a prompt for summarizing the search result by the large language model, The program according to claim 4, wherein by giving the generated prompt to the large language model, the large language model outputs the summarized counterargument.

6. A program for operating a computer including a processor, In a storage unit, each piece of consultation content from a consultant is configured to be managed as a record of a case, The program causes the processor to extracting information to be included in the work product from the information on the consultation content associated with the record of the case; generating a prompt for causing the large language model to output the work product using the extracted information; providing the generated prompt to the large language model and receiving a response from the large language model; presenting the work product as the received response to the user, and managing the contract data in association with the record of the case in the storage unit, generating, in the generating step, a prompt for illustrating the citation relationship of each clause of the contract data, a program that, in the receiving step, receives the illustrated information by providing the prompt to the large language model.

7. The program according to claim 6, wherein the response from the large language model received in the receiving step is stored in the storage unit in association with the record of the case from which the information related to the generation of the prompt is extracted.

8. A method for operating a computer including a processor, wherein the storage unit is configured to manage each of the consultation contents from the consulters as records of cases, and the method includes the processor extracting information to be included in the work product from the information on the consultation content associated with the record of the case; generating a prompt for causing the large language model to output the work product using the extracted information; providing the generated prompt to the large language model and receiving a response from the large language model; presenting the work product as the received response to the user, and managing, in the storage unit, as the record of the case, at least one of the information of the parties involved in the consultation content or the information of the agents in the legal procedure, extracting, in the extracting step, at least one of the information of the parties or the information of the agents. In the step of generating, using at least any one of the information of the extracted party or the information of the agent, as the work product, a prompt is generated to output at least any one of first document data submitted in a litigation procedure, second document data for notifying the legal claims of the parties to the parties, and third document data which is a document regarding the contract conditions agreed between the parties. In the step of receiving, as the output response, at least any one of the first document data, the second document data, and the third document data is received. In the storage unit, information of a term sheet that defines contract conditions is managed as a record of the case. In the step of generating, using the information of the term sheet, a prompt is generated to output a contract as the third document data. In the step of receiving, contract document data as the output response is received. A method.

9. An information processing apparatus, configured to manage each of the consultation contents from a consulter as a record of a case in a storage unit, a control unit of the information processing apparatus, extracting information to be included in the work product from the information of the consultation content associated with the record of the case; generating a prompt for outputting the work product by a large language model using the extracted information; giving the generated prompt to the large language model and receiving a response from the large language model; presenting the work product as the received response to the user. And executing, In the storage unit, at least any one of information of a party related to the consultation content or information of an agent in a legal procedure is managed as a record of the case. In the extracting step, at least any one of the information of the party or the information of the agent is extracted. In the step of generating, using at least any one of the information of the extracted party or the information of the agent, as the work product, a prompt is generated to output at least any one of first document data submitted in a litigation procedure, second document data for notifying the legal claims of the parties to the parties, and third document data which is a document regarding the contract conditions agreed between the parties. In the receiving step, as the output response, at least any one of the first document data, the second document data, and the third document data is received. In the storage unit, information of a term sheet that defines contract conditions is managed as a record of the case. In the generating step, a prompt for outputting a contract as the third document data is generated using the information of the term sheet. An information processing apparatus that receives contract document data as the output response in the receiving step.

10. A method in which a computer including a processor operates, In the storage unit, each of the consultation contents from the consulter is configured to be managed as a record of the case. The method includes the processor extracting information to be included in the work product from the information of the consultation content associated with the record of the case; generating a prompt for outputting the work product by a large language model using the extracted information; giving the generated prompt to the large language model and receiving a response from the large language model; presenting the work product as the received response to the user, and executing. In the storage unit, information of written data describing the claim contents claimed for each argument among the parties regarding the consultation content is managed as a record of the case. The method further includes the processor generating a prompt for outputting a counterargument to the claim contents between the parties in the written data to the large language model; giving the generated prompt to the large language model to cause the large language model to output the counterargument; presenting the output counterargument to the user.

11. An information processing apparatus, In the storage unit, each of the consultation contents from the consulter is configured to be managed as a record of the case. The control unit of the information processing apparatus extracts information to be included in the work product from the information of the consultation content associated with the record of the case; generates a prompt for outputting the work product by a large language model using the extracted information; gives the generated prompt to the large language model and receives a response from the large language model; executing a step of presenting to a user the work product as the received response; in the storage unit, as a record of the case, information of written data describing the content of claims made for each argument between parties regarding the consultation content is managed; the control unit of the information processing apparatus further: generates a prompt for causing the large language model to output a counterargument against the content of claims between parties in the written data; by giving the generated prompt to the large language model, causing the large language model to output the counterargument; An information processing apparatus that presents the output counterargument to a user.

12. A method in which a computer including a processor operates, configured to manage each consultation content from a consultant as a record of a case in a storage unit; the method includes the processor extracting information to be included in the work product from the information of the consultation content associated with the record of the case; generating a prompt for causing the work product to be output by a large language model using the extracted information; giving the generated prompt to the large language model and receiving a response from the large language model; executing a step of presenting to a user the work product as the received response; in the storage unit, contract data is managed in association with a record of a case; in the generating step, generating a prompt for illustrating the citation relationship of each clause of the contract data; In the receiving step, the illustrated information is received by giving the prompt to the large language model.

13. An information processing apparatus, configured to manage each consultation content from a consultant as a record of a case in a storage unit; the control unit of the information processing apparatus extracting information to be included in the work product from the information of the consultation content associated with the record of the case; generating a prompt for causing the work product to be output by a large language model using the extracted information; giving the generated prompt to the large language model and receiving a response from the large language model; executing a step of presenting to a user the work product as the received response; In the memory unit, the data of the contract is managed in association with the record of the case. In the generating step, a prompt for illustrating the citation relationship of each clause of the data of the contract is generated. An information processing apparatus that, in the receiving step, receives the illustrated information by providing the prompt to the large language model.

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