Program, information processing apparatus, method, and system

Abstract

To support creation of a document by a user while suppressing a burden of system construction when there are a plurality of tasks.SOLUTION: A program for causing a computer including a processor and a memory to execute: Analyzing a plurality of documents created in the past in a predetermined task and extracting and storing a plurality of tags for each task, receiving a selection of a task associated with creation of a document, presenting a plurality of tags associated with the selected task, receiving a designation for the presented tags, and inputting a word as the designated tag and an instruction sentence instructing creation of a document using the word to a large-scale language model, A step for outputting a document using words from a large-scale language model and a step for presenting the outputted document using the words are executed.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a program, an information processing device, a method, and a system. [Background technology]

[0002] Technologies for assisting users in creating sentences have been researched and developed. For example, Patent Document 1 discloses a technology for generating sentences containing words specified by a user by using a language model that has been trained on the order of words that appear in a sentence of a contract for learning. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2020-035019 Summary of the Invention [Problem to be solved by the invention]

[0004] However, in the technology disclosed in Patent Document 1, the server learns each sentence of the structured contract for each category and generates a separate language model, which imposes a heavy burden on the system construction including the language model.

[0005] An object of the present disclosure is to support users in creating documents when there are multiple tasks, while reducing the burden of system construction. [Means for solving the problem]

[0006] To solve the above-described problems, one aspect of the present disclosure provides a program for execution by a computer including a processor and a memory. The program causes the processor to execute the following steps: analyzing multiple documents created in the past for a specific task, extracting and storing multiple tags for each task, accepting a selection of a task associated with the creation of the document, presenting multiple tags associated with the selected task, accepting a specification for the presented tags, inputting words as the specified tags and an instruction statement instructing the creation of a document using the words into a large-scale language model, causing the large-scale language model to output a document using the words, and presenting the document using the output words.

[0007] In order to solve the above-described problems, a program according to one aspect of the present disclosure is a program to be executed by a computer including a processor and a memory. The program causes the processor to execute the following steps: analyzing multiple documents created in the past for predetermined tasks, extracting and storing multiple tags for each task, accepting a selection of a task associated with the creation of the document, presenting multiple tags associated with the selected task, accepting a designation for the presented tags and a predetermined image, or a designation for the image, inputting the designated tags and image, or the designated image, and an instruction for creating a document, into a multimodal generative AI model, and causing the multimodal generative AI model to output a document including at least content related to the image, and presenting the output document. [Effects of the Invention]

[0008] According to the present disclosure, when there are multiple tasks, it is possible to support a user in creating documents while reducing the burden of system construction. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a block diagram showing an example of the overall configuration of a system 1. FIG. [Figure 2] 2 is a block diagram showing an example of the configuration of a terminal device 10 shown in FIG. 1. FIG. [Figure 3] 2 is a block diagram showing an example of a functional configuration of a server 20 shown in FIG. 1. FIG. [Figure 4] 4 is a diagram showing the data structure of a user information table 2021 shown in FIG. 3. FIG. [Figure 5] FIG. 4 is a diagram showing the data structure of a document table 2022 shown in FIG. 3. [Figure 6] 4 is a diagram showing the data structure of a tag table 2023 shown in FIG. 3. FIG. [Figure 7] FIG. 4 is a diagram showing the data structure of a prompt table 2024 shown in FIG. 3. [Figure 8] 10 is a flowchart showing an example of the operation of the server 20 when an automatically created document is presented to a user. [Figure 9] FIG. 10 is a schematic diagram showing an example of a display screen of a display 141 when a tag is presented to a user. [Figure 10] 10 is a schematic diagram showing an example of a display screen of a display 141 when an automatically created document is presented to a user. FIG. [Figure 11] FIG. 10 is a schematic diagram showing an example of a display screen of a display 141 when an automatically created document is created. [Figure 12] FIG. 10 is a schematic diagram showing an example of a display screen of a display 141 when related tags are presented to a user. [Figure 13] FIG. 2 is a block diagram showing the basic hardware configuration of a computer 90. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In all drawings describing the embodiments, common components are designated by the same reference numerals, and repeated description will be omitted. Note that the following embodiments do not unduly limit the content of the present disclosure described in the claims. Furthermore, not all components shown in the embodiments are necessarily essential components of the present disclosure. Furthermore, each drawing is a schematic diagram and is not necessarily a precise illustration.

[0011] [1. Overview] The system according to this embodiment analyzes documents previously created for a specific task and extracts tags. When the user creates a document related to the task, the system presents the extracted tags to the user. The tags selected by the user are input into large language models (LLMs), and documents using the words as the selected tags are output from the LLMs.

[0012] There are no particular limitations on the types and contents of documents that can be applied to the system according to this embodiment. Examples of document types include resumes, notifications, contracts, minutes, applications, invoices, certificates, receipts, and reports. In this embodiment, a report will be used as an example of a document type. The report may be in any field, such as a medical report, a business report, or a research report.

[0013] The report describes, for example, the preconditions, the current state, specific aspects, points to note, measures being taken, etc. If the report is a medical report, for example, a nursing record, the preconditions, the current state, specific aspects, points to note, and measures being taken may correspond to, for example, information about the disease being suffered from, the patient's current condition, the state of the patient's life, events that require attention, and the treatments currently being performed, respectively.

[0014] [2. Overall system configuration] Fig. 1 is a block diagram showing an example of the overall configuration of a system 1. The system 1 shown in Fig. 1 includes, for example, a terminal device 10, a server 20, and an NLP system 30. The terminal device 10, the server 20, and the NLP system 30 are communicatively connected via, for example, a network 80.

[0015] 1 shows an example in which the system 1 includes two terminal devices 10, but the number of terminal devices 10 included in the system 1 may be less than three or may be three or more. In FIG. 1, an example in which the system 1 includes one NLP system 30 is shown, but the number of NLP systems 30 included in the system 1 may be two or more.

[0016] 1 shows an example in which the NLP system 30 is independent from the server 20, the server 20 may include the functionality of the NLP system 30. In other words, the server 20 may store the LLM and the NLP model.

[0017] In this embodiment, a collection of multiple devices may be one server 20. The way in which multiple functions required to realize the server 20 according to this embodiment are allocated to one or more pieces of hardware can be determined appropriately depending on the processing capacity of each piece of hardware and / or the specifications required for the server 20.

[0018] The terminal device 10 shown in FIG. 1 is, for example, an information processing device operated by a user who uses a document creation service. The document creation service is provided by a server 20 and an NLP system 30. If the document is, for example, a medical report, the users include nurses, doctors, medical staff, etc. The terminal device 10 is realized by, for example, a mobile terminal such as a smartphone or a tablet. In this embodiment, the terminal device 10 is assumed to be a tablet. The terminal device 10 may also be realized by, for example, a desktop personal computer (PC), a laptop PC, etc.

[0019] The terminal device 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. The input device 13 is a device for receiving input operations from a user (for example, a touch panel, a touch pad, a pointing device such as a mouse, a keyboard, etc.). The output device 14 is a device for presenting information to a user (a display, a speaker, etc.). In this embodiment, the terminal device 10 is assumed to include a touch panel in which the input device 13 and the output device 14 are integrated.

[0020] The server 20 is, for example, an information processing device that provides a document creation service using the NLP system 30. The server 20 is, for example, an information processing device realized by a computer connected to a network 80. As shown in Fig. 1, the server 20 includes a communication IF 22, an input / output IF 23, a memory 25, a storage 26, and a processor 29. The input / output IF 23 functions as an input device for receiving input operations from a user and as an interface for an output device for outputting information to the user.

[0021] The NLP system 30 is, for example, a system in which a natural language model is built. The natural language model is an artificial intelligence model used in the field of natural language processing (NLP), which learns from text data (web pages, books, articles, etc.) to understand patterns of human language and effectively perform natural language generation (NLG) tasks.

[0022] The NLP system 30 includes, for example, an LLM (large-scale language model) and an NLP model. Note that the NLP system 30 may be divided into, for example, a system including an LLM and a system including an NLP model. An LLM is a natural language model constructed by learning large-scale text data, and is used in many NLG tasks such as generating responses to specific questions, automatic sentence generation, text summarization, translation, and sentiment analysis. In addition, an LLM can be used for various purposes such as education, entertainment, customer service, and product development. Examples of LLMs include the following:

[0023] OpenAI ChatGPT (registered trademark) Google Bart (registered trademark) Stable Diffusion Meta Llama 2 midjourney (registered trademark)

[0024] An NLP model is a natural language model that is not an LLM, such as a feedforward neural network or a custom model designed for a particular task or domain.

[0025] The NLP system 30 inputs the text data transmitted from the server 20 into the NLP model or LLM, and causes the NLP model or LLM to output an answer based on the input text data. The NLP system 30 transmits the answer output from the NLP model or LLM to the server 20.

[0026] Each information processing device is configured by a computer 90 (see FIG. 13) equipped with an arithmetic unit and a storage device. The basic hardware configuration of the computer 90 and the basic functional configuration of the computer 90 realized by the basic hardware configuration will be described later. For the terminal device 10, the server 20, and the NLP system 30, descriptions that overlap with the basic hardware configuration and basic functional configuration of the computer 90 will be omitted.

[0027] <2.1 Terminal device configuration> Fig. 2 is a block diagram showing an example of the configuration of the terminal device 10 shown in Fig. 1. As shown in Fig. 2, the terminal device 10 includes a communication unit 120, an input device 13, an output device 14, a storage unit 180, and a control unit 190. The blocks included in the terminal device 10 are electrically connected by, for example, a bus. The terminal device 10 may also include an audio processing unit, a microphone, a speaker, a camera, a position information sensor, or a combination of at least two of these.

[0028] The communication unit 120 performs processing such as modulation and demodulation for the terminal device 10 to communicate with other devices. The communication unit 120 performs transmission processing on signals generated by the control unit 190 and transmits the signals to the outside (for example, the server 20). The communication unit 120 performs reception processing on signals received from the outside and outputs the signals to the control unit 190.

[0029] The input device 13 is a device for a user operating the terminal device 10 to input instructions or information. The input device 13 is realized, for example, by a touch-sensitive device 131 that inputs instructions by touching the operation surface. If the terminal device 10 is a PC or the like, the input device 13 may be realized by a reader, keyboard, mouse, or the like. The input device 13 converts instructions input by the user into electrical signals and outputs them to the control unit 190. The input device 13 may include, for example, a receiving port that receives electrical signals input from an external input device.

[0030] The output device 14 is a device for presenting information to a user operating the terminal device 10. The output device 14 is realized, for example, by a display 141. The display 141 displays various information according to the control of the control unit 190. The display 141 is realized, for example, by an LCD (Liquid Crystal Display) or an organic EL (Electro-Luminescence) display.

[0031] The storage unit 180 is realized by, for example, the memory 15 and the storage 16, and stores data and programs used by the terminal device 10. The storage unit 180 stores, for example, user information 181. The user information 181 includes, for example, various information related to the user who uses the terminal device 10. The various information related to the user includes, for example, the user's name, age, address, date of birth, and contact information.

[0032] The control unit 190 is realized by the processor 19 reading a program stored in the storage unit 180 and executing instructions included in the program. The control unit 190 controls the operation of the terminal device 10. The control unit 190 performs the functions of an operation reception unit 191, a transmission / reception unit 192, and a presentation control unit 193 by operating in accordance with the program.

[0033] The operation reception unit 191 performs processing for receiving instructions or information input from the input device 13. Specifically, the operation reception unit 191 receives instructions or information input from the touch-sensitive device 131. The transmission / reception unit 192 performs processing for the terminal device 10 to transmit and receive data to and from an external device such as the server 20 in accordance with a communication protocol. Specifically, the transmission / reception unit 192 transmits instructions or information input by a user to the server 20. The transmission / reception unit 192 receives information transmitted from the server 20. The presentation control unit 193 controls the output device 14 to present various pieces of information transmitted from the server 20 to the user. For example, the presentation control unit 193 displays multiple tags transmitted from the server 20 on the display 141. Details of the tags will be described later.

[0034] <2.2 Functional configuration of the server> Fig. 3 is a block diagram showing an example of the functional configuration of the server 20 shown in Fig. 1. As shown in Fig. 3, the server 20 performs the functions of a communication unit 201, a storage unit 202, and a control unit 203.

[0035] The communication unit 201 performs processing for communication between the server 20 and external devices. The storage unit 202 includes, for example, a user information table 2021, a document table 2022, a tag table 2023, and a prompt table 2024.

[0036] The tables stored in the storage unit 202 are not limited to these. For example, the document table 2022 may not be stored in the storage unit 202. The services associated with documents may vary depending on their contents. Therefore, documents may be stored for each server that manages the service. Furthermore, documents may be stored in a server related to a service for sharing information among multiple users.

[0037] The user information table 2021 is a table that stores information about users. The document table 2022 is a table that stores information about multiple documents created in a specified task (hereinafter referred to as document information). The document information includes information about multiple documents created in the past in a specified task (hereinafter referred to as past document information). The tag table 2023 is a table that stores multiple tags. The prompt table 2024 is a table that stores information about instruction statements that are input statements to the NLP system 30. Details of these tables will be described later.

[0038] The control unit 203 is realized by the processor 29 reading a program stored in the storage unit 202 and executing instructions included in the program. The program includes an application such as a web browser application. The program includes a programming language such as JavaScript (registered trademark) that is executed on the web browser application stored in the terminal device 10. The control unit 203 operates in accordance with the program to fulfill the functions of a reception control module 2031, a transmission control module 2032, a service processing module 2033, and a presentation control module 2034.

[0039] The reception control module 2031 controls the process of the server 20 receiving signals from external devices in accordance with a communication protocol. The transmission control module 2032 controls the process of the server 20 transmitting signals to external devices in accordance with a communication protocol.

[0040] The service processing module 2033 analyzes a plurality of documents created in the past for a predetermined task, and controls the process of extracting and storing a plurality of tags for each task. Specific examples of tasks will be described later.

[0041] Specifically, the service processing module 2033 transmits the past document information read from the document table 2022 to the NLP system 30 via the transmission control module 2032. The document table 2022 stores, for example, past document information for each of a plurality of types of tasks.

[0042] At this time, the service processing module 2033 may transmit a predetermined instruction statement along with the past document information depending on the performance and characteristics of the NLP model, the content and amount of information of the past document information, etc. The predetermined instruction statement is a prompt that instructs the NLP model included in the NLP system 30 to extract multiple tags. In this case, for example, a second prompt table (not shown) stored in the storage unit 202 may store default predetermined instruction statements with different contents for multiple types of tasks. The service processing module 2033 may, for example, read out from the second prompt table a predetermined instruction statement associated with the type of task to which the past document information is linked, and transmit it to the NLP system 30 together with the past document information.

[0043] The NLP system 30 receives past document information transmitted from the transmission control module 2032, inputs it into an NLP model, and causes the NLP model to output multiple tags. The NLP model is a natural language model that is trained to extract specific words from multiple documents as tags when the documents are input. Specific examples of tags will be described later.

[0044] The NLP system 30 transmits a plurality of tags output from the NLP model to the server 20. The service processing module 2033 receives the plurality of tags transmitted from the NLP system 30 via the reception control module 2031 and stores them in the tag table 2023. The service processing module 2033 executes this series of processes for all of the past document information linked to each of the plurality of types of tasks.

[0045] Note that the service processing module 2033 does not need to use an NLP model to extract multiple tags. For example, the service processing module 2033 may perform rule-based natural language analysis such as lexical semantic analysis on multiple documents created in the past for a specific task. The service processing module 2033 may then extract multiple tags using such well-known natural language analysis. Also, for example, the service processing module 2033 may extract tags using an LLM instead of an NLP model.

[0046] The service processing module 2033 inputs a word as a tag specified by the user and an instruction statement into the LLM, and causes the LLM to output a document using the word (hereinafter referred to as an automatically generated document). The instruction statement is a prompt that instructs the LLM to generate an automatically generated document. Details of tag specification by the user will be described later. The LLM may be tuned so that when a specific word is input as a tag, a document using the word is generated.

[0047] Specifically, the service processing module 2033 transmits tags specified by the user and instruction sentences read from the prompt table 2024 and edited to the NLP system 30 via the transmission control module 2032. The tag table 2023 stores, for example, multiple tags extracted by an NLP model for each of multiple types of tasks. The prompt table 2024 stores, for example, partially defaulted instruction sentences with different contents for each of multiple types of tasks. In other words, multiple tags and instruction sentences are associated with each of multiple types of tasks. Blank portions in the instruction sentences that are not defaulted are completed by, for example, specifying tags by the user. Details of this completion will be described later.

[0048] The NLP system 30 receives the tag and instruction sent from the transmission control module 2032, inputs them to the LLM, and causes the LLM to output an automatically created document. In other words, the service processing module 2033 causes the NLP system 30 to output an automatically created document.

[0049] It is not essential to input a command to the LLM using the prompt table 2024. For example, a command may be input to the input device 13, and the service processing module 2033 or the transmission control module 2032 may transmit the command to the NLP system 30.

[0050] The presentation control module 2034 controls the process of presenting information to the user. For example, the presentation control module 2034 reads out multiple tags associated with a task selected by the user from the tag table 2023 and controls the process of presenting the tags to the user. Details of the user's task selection will be described later. Also, for example, the presentation control module 2034 controls the process of presenting an automatically created document output from the LLM to the user.

[0051] [3 Data Structure] 4 to 7 are diagrams showing the data structures of tables stored in the server 20. Note that Figures 4 to 7 are merely examples and do not exclude data that is not listed. Furthermore, even data that is listed in the same table may be stored in separate storage areas in the storage unit 202.

[0052] Fig. 4 is a diagram showing the data structure of the user information table 2021. The user information table 2021 shown in Fig. 4 is a table having columns of name, age, sex, date of birth, and contact information, with the user ID as a key.

[0053] The user ID is an item that stores an identifier for uniquely identifying a user. The name is an item that stores the name of the user. The age is an item that stores the age of the user. The gender is an item that stores the gender of the user. The date of birth is an item that stores the date of birth of the user. The contact information is an item that stores the contact information (e.g., telephone number, email address, etc.) of the terminal device 10 that the user has.

[0054] Fig. 5 is a diagram showing the data structure of the document table 2022. The document table 2022 shown in Fig. 5 is a table having columns of user ID, date and time, document data, task, and type ID, with the document ID as a key.

[0055] The document ID is an item that stores an identifier for uniquely identifying a document. The user ID is an item that stores an identifier for uniquely identifying the person who created the document. The "user ID" item in the document table 2022 corresponds to the "user ID" item in the user information table 2021, for example. Note that the "user ID" item may store the name of the document creator instead of the aforementioned identifier. The date and time is an item that stores the date and time the document was created.

[0056] Document data is an item that stores data related to documents, i.e., document information. Document data is created by a creator by summarizing, in text, the underlying situation, current status, specific aspects, points to note, and adopted countermeasures, for example. Document data includes data related to past documents in a specified task, i.e., past document information. Document data may include, along with text, specified numerical tables, photographs, videos, etc., or at least any combination of these. The item "Document Data" may also store reference information (path) to a document data file located elsewhere.

[0057] The "task" is an item that stores the type of task associated with the creation of a document. For example, if the document is a medical report, the "task" item stores patient reception / registration, patient condition assessment / diagnosis, prescription, drug management, treatment / procedure, nursing care, or conference / meeting. For example, if the document is a business report, the "task" item stores business plan creation, legal procedure execution, fundraising, human resource acquisition / management, product / service development, marketing, sales, financial accounting, or risk management. For example, if the document is a research report, the "task" item stores research plan development, literature research, experiments, data collection, data analysis, result reporting, presentation / publication, or ethical considerations (protection of personal information, ensuring the rights of research participants, etc.).

[0058] The type ID is an item that stores an identifier for uniquely identifying the type of document. The document types include, for example, medical reports, business reports, research reports, etc. The item "type ID" stores an identifier that can identify the type of these reports. In this embodiment, information linked to all type IDs is stored together in one document table 2022, but, for example, a document table for each type ID may be stored in the storage unit 202.

[0059] Fig. 6 is a diagram showing the data structure of the tag table 2023. The tag table 2023 shown in Fig. 6 is a table having columns of tag data, task, and type ID, with the tag ID as a key.

[0060] The tag ID is an item that stores an identifier for uniquely identifying multiple tags associated with a specific task. The tag data is an item that stores multiple pieces of data related to tags associated with a specific task. The tag data is, for example, text data of words as tags.

[0061] For example, if the type of task linked to a medical report is nursing care, the "tag data" item stores evaluation, goal, intervention, intervention plan, etc. For example, if the type of task linked to a medical report is diagnosis, the "tag data" item stores diagnosis, condition, test results, treatment plan, prognosis, etc. For example, if the type of task linked to a business report is marketing, the "tag data" item stores segmentation, loyalty, awareness, targeting, positioning, customer experience, persona, insight, etc. For example, if the type of task linked to a research report is experiment, the "tag data" item stores experimental design, experimental conditions, objectives, methods, materials, measurements, results, analysis, conclusions, references, etc.

[0062] In the example of FIG. 6, the column for the item "Tag Data" is divided into a column for the item "Technical Term" and a column for the item "General Term." The item "Technical Term" stores information about technical terms in the field to which the task belongs as information about tags. The item "General Term" stores information about general terms that can be used in fields other than the field to which the task belongs as information about tags. Note that it is not essential that the column for the item "Tag Data" be divided into a column for the item "Technical Term" and a column for the item "General Term." For example, a mixture of technical term tags and general term tags may be stored together in the column for the item "Tag Data."

[0063] The "task" field stores the type of task to which multiple tags are linked. The "task" field in the tag table 2023 corresponds, for example, to the "task" field in the document table 2022. The "type ID" field stores an identifier for uniquely identifying the type of document from which multiple tags are extracted. The "type ID" field in the tag table 2023 corresponds, for example, to the "type ID" field in the document table 2022.

[0064] Fig. 7 is a diagram showing the data structure of the prompt table 2024. The prompt table 2024 shown in Fig. 7 is a table having columns of prompt data, document name, task, and type ID, with a prompt ID as a key.

[0065] The prompt ID is an item that stores an identifier for uniquely identifying an instruction. The prompt data is an item that stores data related to an instruction. Data related to an instruction is, for example, text data of an instruction that is partially blank. For example, the text data of an instruction is as follows: "Please create △△△ (blank part: document name) containing 〇〇〇 (blank part: tag word)."

[0066] The "prompt data" item may store, for example, reference information (path) for a prompt data file stored in another storage area. For example, the text data of the instruction statement stored in the "prompt data" item may have a blank section for storing an outline of the manager / executor of the task associated with the creation of the automatically created document. The manager / executor of the task may be, for example, a hospital if the automatically created document is a medical report, a company if the automatically created document is a business report, or a research institute if the automatically created document is a research report. The outline of the manager / executor of the task may include, for example, the industry, business content, organizational structure, history, number of employees, capital, sales, etc. In this case, the prompt table 2024 may store, for example, information regarding the outline of the manager / executor of the task.

[0067] The document name is an item that stores the name of the document that the instruction statement instructs to create. For example, if the task is nursing care, the "document name" item stores the name of the nursing record, nursing plan, care report, instruction record, etc. The task is an item that stores the type of task that the instruction statement is associated with. The "task" item in the prompt table 2024 corresponds, for example, to the "task" item in the document table 2022 and the tag table 2023. The type ID is an item that stores an identifier for uniquely identifying the type of automatically created document. The "type ID" item in the prompt table 2024 corresponds, for example, to the "type ID" item in the document table 2022 and the tag table 2023.

[0068] [4 actions] The operation of the server 20 when presenting an automatically created document to a user will be described. FIG. 8 is a flowchart showing an example of the operation of the server 20 when presenting an automatically created document to a user. In the explanation of FIG. 8, the server 20 provides a service for creating an automatically created document as SaaS (Software as a Service). In this case, the specified task is, for example, nursing care, and the target document is, for example, a nursing record. Information regarding past nursing records (past document information) is stored, for example, in the document table 2022.

[0069] First, the service processing module 2033 stores information about the immediately previous automatically created document edited by the user, together with the corresponding task type, in the document table 2022. The immediately previous automatically created document is the automatically created document that was output from the LLM and presented to the user by the execution of the previous process shown in Figure 8. In other words, the service processing module 2033 adds the information about the immediately previous automatically created document to the past document information stored in the document table 2022.

[0070] In step S11, the server 20 analyzes multiple documents created in the past for a specific task, and extracts and stores multiple tags for each task (storing step). Specifically, for example, the service processing module 2033 reads out past document information to which information about the immediately previous automatically created document has been added from the document table 2022. The service processing module 2033 transmits the read past document information to the transmission control module 2032. The transmission control module 2032 receives the past document information transmitted from the service processing module 2033 and transmits it to the NLP system 30.

[0071] The NLP system 30 receives the past document information transmitted from the transmission control module 2032, inputs it into the NLP model, and causes the NLP model to output a plurality of tags. The NLP system 30 transmits the plurality of tags output from the NLP model to the server 20.

[0072] When the NLP system 30 outputs multiple tags from the NLP model, that is, when the server 20 extracts multiple tags, the server 20 may extract the multiple tags at a predetermined timing, for example.

[0073] 8, the server 20 extracts multiple tags every time a new document is created in a predetermined task. Specifically, every time the previous automatically created document (new document) linked to nursing care (predetermined task) is created and information about the automatically created document is added to the tag table 2023, the service processing module 2033 extracts multiple tags using the NLP system 30. This allows the past document information stored in the tag table 2023 to be updated in a timely manner, thereby fully meeting user needs in tag specification when creating an automatically created document.

[0074] The predetermined timing does not have to be every time a new document is created in a predetermined task. For example, the server 20 may extract multiple tags at a predetermined cycle. Specifically, the service processing module 2033 may read past document information from the document table 2022 at a predetermined cycle and transmit it to the NLP system 30 to extract multiple tags. The predetermined cycle can be set arbitrarily. This allows multiple tags to be extracted using updated past document information, thereby fully meeting user needs in tag specification when creating automatically created documents.

[0075] The reception control module 2031 receives multiple tags transmitted from the NLP system 30 and transmits them to the service processing module 2033. The service processing module 2033 receives the multiple tags transmitted from the reception control module 2031, associates the past document information read by the service processing module 2033 with the type of task to which it is linked, and stores the tags in the tag table 2023.

[0076] When storing multiple tags in the tag table 2023, the server 20 may, for example, analyze the extracted multiple tags and store them in a manner according to the analysis results. For example, the server 20 may analyze the extracted multiple tags and store them in a hierarchy based on the analysis results. This improves the user's convenience in specifying tags when creating an automatically created document.

[0077] Specifically, for example, the service processing module 2033 may analyze a plurality of tags received from the reception control module 2031 and classify them into specialized terms in the medical field (particularly nursing) and general terms that can be used in other fields. When classifying the tags, the service processing module 2033 may use, for example, a predetermined dictionary tool. Using a dictionary tool improves the accuracy of the classifying, thereby further improving the convenience for the user when specifying tags when creating an automatically created document.

[0078] The type of dictionary tool is not particularly limited, and known dictionary tools such as WordNet, GloVe (Global Vectors for Word Representation), NER (Stanford Named Entity Recognizer), and Pattern may be used. A predetermined dictionary tool may be updated as needed. Furthermore, the predetermined dictionary tool may learn new information in response to user operations.

[0079] The service processing module 2033 may store the analyzed tags in a hierarchical structure of technical terms and general terms in the tag table 2023. In this case, the tag table 2023 may have a column for the item "tag data" divided into a column for the item "technical term" and a column for the item "general term," as shown in Fig. 6, for example.

[0080] The hierarchical classification is not limited to the classification of technical terms and general terms, and may be any classification that allows the user to easily specify tags. Furthermore, the service processing module 2033 may store the analyzed tags in the tag table 2023 in a classification other than the hierarchical classification (for example, grouping tags according to the degree of relevance).

[0081] In step S12, the server 20 accepts the selection of a task linked to the creation of a document (step of accepting a selection). In this embodiment, the server 20 accepts the selection of nursing care linked to the creation of a nursing record. Specifically, for example, the operation accepting unit 191 accepts the selection of a task by a selection operation by the user on the input device 13. The operation accepting unit 191 transmits information on the type of task input to the input device 13 to the transmitting / receiving unit 192. The transmitting / receiving unit 192 receives the information on the type of task transmitted from the operation accepting unit 191 and transmits it to the server 20. The reception control module 2031 receives the information on the type of task transmitted from the terminal device 10. In this way, the server 20 accepts the user's selection of a task linked to the creation of a document.

[0082] 8, the server 20 executes the process of step S11 and the process of step S12 consecutively, but this is not limiting. For example, the server 20 may execute the process of step S11 separately from the processes from step S12 onwards.

[0083] In step S13, the server 20 presents multiple tags associated with the selected task (multiple presenting step). Specifically, for example, the reception control module 2031 transmits information regarding the task type received from the terminal device 10 to the service processing module 2033. Based on the information regarding the task type received from the reception control module 2031, the service processing module 2033 searches the tag table 2023 for tasks of the same type as the task selected by the user, and reads out multiple tags associated with the tasks of the same type. The service processing module 2033 transmits the read out multiple tags to the presentation control module 2034.

[0084] The presentation control module 2034 receives the multiple tags transmitted from the service processing module 2033, and transmits the multiple tags and a first switching command to switch the display screen of the display 141 to the document creation screen 142 shown in Fig. 9 to the terminal device 10. The transmission / reception unit 192 receives the multiple tags and the first switching command transmitted from the presentation control module 2034, and transmits them to the presentation control unit 193. Based on the multiple tags and the first switching command received from the transmission / reception unit 192, the presentation control unit 193 switches the display screen of the display 141 to the document creation screen 142, and displays the multiple tags on the document creation screen 142.

[0085] There is no particular rule between the timing of switching to document creation screen 142 under the control of presentation control unit 193 and the timing of displaying multiple tags on document creation screen 142. However, it is preferable that multiple tags are displayed on document creation screen 142 at least at the time of switching to document creation screen 142.

[0086] In this embodiment, the presentation control module 2034 presents multiple tags associated with the selected task on the document creation screen 142 in a presentation format according to the analysis results. Details of the document creation screen 142 will be described below with reference to Fig. 9. Fig. 9 is a schematic diagram showing an example of the display screen of the display 141 when tags are presented to the user.

[0087] 9 includes, for example, a task button 1411, a task selection box 1412, a document selection box 1413, a tag specification box 1414, and a start button 1415. In the initial state of the document creation screen 142, for example, nothing is displayed in the task selection box 1412, the document selection box 1413, and the tag specification box 1414.

[0088] The task button 1411 is a button for displaying multiple types of tasks in the task selection box 1412. When the task button 1411 is pressed, the operation reception unit 191 transmits reception information indicating that the press has been received to the server 20. The presentation control module 2034, which has received the reception information, reads out multiple types of tasks from the document table 2022 or the tag table 2023 and transmits them to the terminal device 10. The presentation control unit 193, which has received the multiple types of tasks, displays the multiple types of tasks in the task selection box 1412.

[0089] When a specific type of task is selected from the multiple types of tasks displayed in the task selection box 1412, the operation receiving unit 191 transmits task information related to the specific type of task whose selection has been received to the server 20. In the example of Fig. 9, nursing care is selected as the specific type of task.

[0090] The presentation control module 2034, which has received the task information, reads out the document name of the document linked to the specific type of task from the prompt table 2024 and transmits it to the terminal device 10. The presentation control module 2034 also reads out multiple tags associated with the specific type of task from the tag table 2023 and transmits them to the terminal device 10.

[0091] The presentation control unit 193, which has received the document name, displays the document name in the document selection box 1413. Furthermore, the presentation control unit 193, which has received multiple tags, displays the multiple tags in the tag specification box 1414. In the example of FIG. 9, multiple document names linked to nursing care are displayed in the document selection box 1413, and multiple tags associated with nursing care are displayed in the tag specification box 1414.

[0092] In the example of FIG. 9, the presentation control unit 193 provides a column for technical terms and a column for general terms in the tag specification box 1414, and displays the corresponding tags in each column. This allows the user to easily select tags. The display manner of the hierarchical division of technical terms and general terms is not limited to the example of FIG. 9. For example, technical terms may be displayed in a large size, and general terms may be displayed in a small size. Furthermore, for example, only technical terms may be displayed in bold, or technical terms may be displayed in red, and general terms may be displayed in black. Alternatively, two or more of these may be displayed in combination.

[0093] 9, the presentation control module 2034 controls the presentation control unit 193 to display the document creation screen 142, on which multiple tags are displayed, on the display screen of the display 141, whereby the server 20 presents multiple tags associated with the task selected by the user. Note that the screen example shown in FIG. 9 is merely an example, and the document creation screen 142 may employ various screen configurations and UI elements.

[0094] In step S14, the server 20 accepts a designation for the presented tag (designation acceptance step). In this embodiment, the server 20 accepts a designation of a specific tag from among multiple tags associated with nursing care displayed on the document creation screen 142. The number of specific tags to be designated may be, for example, one or more. Specifically, for example, the operation acceptance unit 191 accepts a designation of a specific tag displayed on the document creation screen 142 through a designation operation by the user on the input device 13. The operation acceptance unit 191 transmits information about the specific tag whose designation has been accepted to the transmission / reception unit 192. The transmission / reception unit 192 receives the information about the specific tag transmitted from the operation acceptance unit 191 and transmits it to the server 20. The reception control module 2031 receives the information about the specific tag transmitted from the terminal device 10. As a result, the server 20 accepts a user's designation for the presented specific tag.

[0095] In the example of FIG. 9, nursing records are selected from the document names displayed in the document selection box 1413, and nursing, treatment, and patient are specified from the multiple tags displayed in the tag specification box 1414.

[0096] In step S15, the server 20 inputs the word and instruction sentence as the specified tag into the LLM and causes the LLM to output an automatically created document (output step). Specifically, for example, the reception control module 2031 transmits information about the specific tag received from the terminal device 10 to the service processing module 2033. The service processing module 2033 reads data about the specific instruction sentence from the prompt table 2024 based on the information about the specific tag received from the reception control module 2031.

[0097] In more detail, for example, the service processing module 2033 searches the prompt table 2024 for a task of the same type as the task type associated with a specific tag. Then, the service processing module 2033 reads data on a specific instruction associated with the task of the same type from the prompt table 2024. In other words, the information on a specific tag includes information on the type of task associated with the specific tag.

[0098] The service processing module 2033 completes the instruction sentence by editing the data related to the read specific instruction sentence. In detail, for example, the service processing module 2033 completes the instruction sentence by applying specific tags to blank parts of the read text data and adjusting the expressions so that the sentence does not sound out of place.

[0099] The service processing module 2033 transmits the specific tag received from the reception control module 2031 and the specific instruction text completed by editing the text data read from the prompt table 2024 to the transmission control module 2032. The transmission control module 2032 receives the specific tag and the specific instruction text transmitted from the service processing module 2033 and transmits them to the NLP system 30.

[0100] The NLP system 30 receives the specific tag and specific instruction sent from the transmission control module 2032, inputs them into the LLM, and causes the LLM to output an automatically created document. As a result, the server 20 inputs the word as the specific tag and the specific instruction into the LLM, and causes the LLM to output an automatically created document.

[0101] In the example of Figure 9, when a specific document name is selected from the document names displayed in the document selection box 1413, a specific tag is specified from the multiple tags displayed in the tag specification box 1414, and the start button 1415 is pressed, an automatically created document is output.

[0102] The start button 1415 is a button for starting the creation of an automatically created document, that is, for causing the LLM to output the automatically created document. When the start button 1415 is pressed, the operation reception unit 191 receives the selection of a specific document name, the designation of a specific tag, and the press, and transmits each piece of information related to the specific document name and the specific tag to the server 20. The service processing module 2033, which has received each piece of information related to the specific document name and the specific tag, transmits the specific tag read from the tag table 2023 and the instruction statement (instructing the creation of a specific document) read from the prompt table 2024 and edited, to the NLP system 30. The service processing module 2033 then causes the LLM to output the automatically created document.

[0103] In step S16, the server 20 presents the output automatically generated document (presenting step). Specifically, for example, the NLP system 30 transmits the automatically generated document that it has caused the LLM to output to the server 20. The reception control module 2031 receives the automatically generated document transmitted from the NLP system 30, associates information about the automatically generated document with a task, and stores it in the document table 2022. The reception control module 2031 also transmits the received automatically generated document to the presentation control module 2034.

[0104] The presentation control module 2034 receives the automatically created document transmitted from the service processing module 2033, and transmits the automatically created document and a second switching command to switch the display screen of the display 141 to the document confirmation screen 143 shown in Fig. 10 to the terminal device 10. The transmission / reception unit 192 receives the automatically created document and the second switching command transmitted from the presentation control module 2034, and transmits them to the presentation control unit 193. Based on the automatically created document and the second switching command received from the transmission / reception unit 192, the presentation control unit 193 switches the display screen of the display 141 to the document confirmation screen 143, and displays the automatically created document on the document confirmation screen 143.

[0105] There is no particular rule between the timing of switching to document confirmation screen 143 under the control of presentation control unit 193 and the timing of displaying the automatically created document on document confirmation screen 143. However, it is preferable that the automatically created document is displayed on document confirmation screen 143 at least at the time of switching to document confirmation screen 143.

[0106] Details of document confirmation screen 143 will be described below with reference to Fig. 10. Fig. 10 is a schematic diagram showing an example of the display screen of display 141 when an automatically created document is presented to the user.

[0107] On the document confirmation screen 143 shown in Fig. 10, for example, an automatically created document is displayed in area 1431. In the example of Fig. 10, as a result of a user operation on the document creation screen 142 shown in Fig. 9, a nursing record format is displayed in area 1431. Note that the format shown in Fig. 10 is merely an example, and the LLM can output automatically created documents in formats of various types and contents.

[0108] The document confirmation screen 143 has, for example, an edit start button 1433 and a print button 1434 in an area 1432. The edit start button 1433 is a button for editing an automatically created document. When the edit start button 1433 is pressed, the operation acceptance unit 191 accepts the press, and the presentation control unit 193 makes the automatically created document displayed in the area 1431 editable. This allows the user to edit the automatically created document displayed in the area 1431 to the desired content, format, etc., thereby fully meeting user needs.

[0109] The presentation control unit 193 transmits the edited automatically created document to the server 20. The service processing module 2033 stores the received edited automatically created document in the document table 2022. As a result, the service processing module 2033 updates the automatically created document stored in the document table 2022.

[0110] The print button 1434 is a button for printing out the automatically created document displayed in the area 1431. When the print button 1434 is pressed, the operation reception unit 191 receives the press, and the presentation control unit 193 transmits the automatically created document to, for example, a printer (not shown). The printer is wirelessly connected to, for example, the terminal device 10, and prints out the automatically created document received from the presentation control unit 193.

[0111] 10, the presentation control module 2034 controls the presentation control unit 193 to display the document confirmation screen 143, which displays the automatically created document, on the display screen of the display 141, thereby causing the server 20 to present the automatically created document that has been output by the LLM. Note that the screen example shown in Fig. 10 is merely an example, and the document confirmation screen 143 may employ various screen configurations and UI elements.

[0112] Hereinafter, other examples of the document creation screen 142 and the document confirmation screen 143 will be described with reference to Fig. 11. Fig. 11 is a schematic diagram showing an example of the display screen of the display 141 when an automatically created document is created. In the example shown in Fig. 11, it is assumed that the type of task to which the automatically created document is linked has been selected in advance, and the type of the automatically created document (work report) has been determined.

[0113] In the example shown in Fig. 11(a), the automatically created document is in a format for inputting both pre-work and post-work report contents. Note that the format of the automatically created document is not limited to this, and it may be a format for inputting only post-work report contents, or a format for inputting each of pre-work, during-work, and post-work report contents.

[0114] When the operation receiving unit 191 receives a tap from the user on an inputtable area, the presentation control module 2034 controls the presentation control unit 193 to display a report form for inputting report content into that area on the display screen of the display 141. Specifically, for example, when the operation receiving unit 191 receives a tap on the first editing area 1416 located below "Before work", the presentation control module 2034 displays a report form for inputting report content into the first editing area 1416.

[0115] 11(b) is a schematic diagram showing a report form for inputting report content into a predetermined area. In the example shown in FIG. 11(b), the presentation control module 2034 controls the presentation control unit 193 to display a first editing area 14161 and a second editing area 14162 on the display screen of the display 141. The first editing area 14161 is an area for attaching an image. The second editing area 14162 is an area for presenting a plurality of tags extracted by the server. The image attached to the first editing area 14161 may be stored in, for example, the storage unit 180 or the storage unit 202.

[0116] 11(b), to attach an image to the first editing area 14161, the user taps on the first editing area 14161. When the operation accepting unit 191 accepts the tap on the first editing area 14161, the presentation control module 2034 controls, for example, the presentation control unit 193 to display a selection window (not shown) for an image to be attached to the first editing area 14161. The user selects a specific image to be attached to the first editing area 14161 from a plurality of images displayed in a list in the selection window. When the operation accepting unit 191 accepts the user selection, the presentation control module 2034 reads out the specific image from the storage unit 180 or the storage unit 202 and controls the presentation control unit 193 to attach the specific image to the first editing area 14161.

[0117] 11(b), to display multiple tags in the second editing area 14162, the user taps the second editing area 14162. When the operation receiving unit 191 receives the tap on the second editing area 14162, the presentation control module 2034 reads out multiple tags associated with the type of task selected in advance from, for example, the tag table 2023. Then, the presentation control module 2034 controls the presentation control unit 193 to display the read-out multiple tags in the second editing area 14162.

[0118] 11(c) is a schematic diagram showing an example of input to the report form. In the example shown in FIG. 11(c), a specific image is attached to a first editing area 14161. Furthermore, a plurality of tags extracted by the server 20 are displayed in a second editing area 14162. The user can specify the plurality of tags displayed in the second editing area 14162 by tapping a specific tag from among the plurality of tags and the operation receiving unit 191 receiving the tap operation. When input of the report content is completed, the user presses a button 14163.

[0119] Fig. 11(d) is a schematic diagram showing an example of the display of the created report. In the example shown in Fig. 11(d), an automatically created document with both pre-work and post-work report contents entered is displayed on the display screen of the display 141.

[0120] [5 Summary] As described above, in this embodiment, the service processing module 2033 inputs past document information into the NLP model for each task, extracts multiple tags for each task, and stores them in the tag table 2023. The reception control module 2031 accepts the selection of a task associated with document creation, accepted by the operation acceptance unit 191. The presentation control module 2034 controls the presentation control unit 193 to present multiple tags associated with the task selected by the user. The reception control module 2031 accepts the user's designation of tags, accepted by the operation acceptance unit 191. The service processing module 2033 inputs the specified tag words and instruction sentences into the LLM to create an automatically created document. The presentation control module 2034 controls the presentation control unit 193 to present the automatically created document.

[0121] This allows for the creation of automated documents for each task using a single NLP model and a single LLM, even when there are multiple types of tasks. Therefore, even when there are multiple types of tasks, it is possible to support users in creating documents while reducing the burden of system construction.

[0122] Furthermore, since information about automatically created documents is also past document information, it is possible to use an NLP model to timely update multiple tags stored in the tag table 2023. This makes it possible to fully meet user needs in tag specification when creating a new automatically created document.

[0123] [6. Modifications] <6.1 First Modification> In the present embodiment, an example has been described in which the server 20 analyzes and hierarchically classifies the extracted tags. Here, in addition to classifying the tags into levels, the server 20 may also group the tags, for example.

[0124] Specifically, for example, the server 20 may analyze the extracted tags and store the tags in groups based on the analysis results. More specifically, the service processing module 2033 may analyze the tags received from the reception control module 2031, extract two or more tags with high relevance, and group them. "High relevance" refers to two or more tags having high relevance to each other in terms of their semantic content as words.

[0125] The service processing module 2033 may store the analyzed tags in a grouped state in addition to being hierarchically divided into technical terms and general terms in the tag table 2023. In this case, the tag table 2023 may store the analyzed tags in a grouped state in addition to being divided into a column for the item "Tag Data" as shown in Fig. 6, and may also store the analyzed tags in a column for two or more groups, such as "Group 1, Group 2, ...".

[0126] Furthermore, for example, the server 20 may display tags related to the tag specified by the user. More specifically, the operation receiving unit 191 transmits information about the specific tag for which the user's designation has been received to the server 20 via the transmitting / receiving unit 192. When the reception control module 2031 receives information about the specific tag transmitted from the terminal device 10, the reception control module 2031 may transmit the information about the specific tag to the presentation control module 2034 instead of the service processing module 2033.

[0127] The presentation control module 2034 may use the information about the specific tag received from the reception control module 2031 to search the tag table 2023 for a group to which the specific tag belongs, and read out tags other than the specific tag (hereinafter, related tags) from the group. The presentation control module 2034 transmits the read related tags to the terminal device 10 via the transmission control module 2032. The presentation control unit 193 displays the related tags received via the transmission / reception unit 192 on the document creation screen 144.

[0128] Details of document creation screen 144 will be described below with reference to Fig. 12. Fig. 12 is a schematic diagram showing an example of a display screen of display 141 when related tags are presented to the user. Document creation screen 144 shown in Fig. 12 has the same screen configuration and content as document creation screen 142 shown in Fig. 9, except that it has related tag specification box 1416.

[0129] On document creation screen 144, when a specific tag is specified from among the multiple tags displayed in tag specification box 1414, related tags related to the specific tag are displayed in related tag specification box 1416. In other words, on document creation screen 144 in its initial state, nothing is displayed in related tag specification box 1416.

[0130] 12, the presentation control module 2034 controls the presentation control unit 193 to link a specific tag designated by the user with related tags associated with the specific tag and display them on the display 141. This allows the user to designate a specific tag and related tags at once on one screen, improving user convenience.

[0131] The presentation control module 2034 may, for example, display a specific tag and related tags in close proximity and in a linked manner in one box (not shown) on the document creation screen 144. Also, for example, displaying a specific tag and related tags in a linked manner is not essential, and the presentation control module 2034 may display related tags on a screen separate from the screen on which the specific tag is displayed. Furthermore, the server 20 may receive a designation by the operation receiving unit 191 receiving a designation of at least one of a specific tag and related tags on the document creation screen 144 by a flick operation. This improves the efficiency of tag designation, thereby improving user convenience.

[0132] <6.2 Second Modification> In this specification, the term "task" is a concept that includes not only an activity, work, or job aimed at a specific purpose / goal, such as nursing care, fundraising, data analysis, etc., but also documents created in the course of the activity, work, or job. Therefore, the server 20 may extract and store multiple tags for each type of document, for example.

[0133] Specifically, for example, the document table 2022 may store the document name for each document type in the item "task." The service processing module 2033 may, for example, input past document information for each document type into an NLP model and output multiple tags from the NLP model for each document type. The service processing module 2033 may, for example, store the multiple tags output from the NLP model in the tag table 2023 for each document type. In other words, the tag table 2023 may, for example, store the document name for each document type in the item "task."

[0134] <6.3 Third Modification> In this embodiment, an example has been described in which the server 20 inputs a word as a designated tag and an instruction sentence into the LLM to create an automatically created document. However, the server 20 may use an image instead of the word as a designated tag when creating an automatically created document. In this case, the image may be a still image or a video.

[0135] The server 20 may, for example, analyze multiple documents created in the past for a specific task and extract and store multiple images for each task. Specifically, for example, the service processing module 2023 may input past document information for each task into a first multimodal generation AI model and cause the first multimodal generation AI model to output multiple images for each task. The first multimodal generation AI model is a multimodal generation AI model provided in the NLP system 30 instead of an NLP model. The service processing module 2023 may, for example, store the multiple images output by the first multimodal generation AI model in an image table (not shown) for each task. The image table may, for example, be stored in the storage unit 202 instead of the tag table 2023, and may have the same table structure as the tag table 2023, except that the item "tag data" is replaced with the item "image data."

[0136] Similar to the example of this embodiment, the server 20 accepts the selection of a task linked to the creation of a document. The server 20 may, for example, present multiple images associated with the selected task. Specifically, for example, the service processing module 2033 may search the image table for tasks of the same type as the task selected by the user, and read multiple images associated with the tasks of the same type. The presentation control module 2034 may, for example, transmit the multiple images received from the service processing module 2033 to the terminal device 10 and display the multiple images on the display screen of the display 141.

[0137] The server 20 may, for example, accept a designation for a presented image. Specifically, for example, the operation acceptance unit 191 may accept a designation of a specific image (which may be one or more images) displayed on the display screen of the display 141, by a designation operation by the user on the input device 13. The transmission / reception unit 192 may, for example, transmit information relating to the specific image received from the operation acceptance unit 191 to the server 20. For example, the server 20 may accept a user's designation for a presented specific image by the reception control module 2031 receiving information relating to the specific image transmitted from the terminal device 10.

[0138] For example, the server 20 may input a specified image and an instruction statement instructing the creation of a document including content related to the image into the multimodal generative AI model, and cause the multimodal generative AI model to output a document including content related to the image. A "document including content related to the image" is an example of an automatically created document, and may be a document that includes the image itself, or a document in which the content displayed in the image is converted into text and reflected. In other words, a "document including content related to the image" does not necessarily have to include the image itself.

[0139] Specifically, for example, the service processing module 2033 may read and edit data related to a specific instruction from the prompt table 2024 based on information about a specific image received from the reception control module 2031, to complete the instruction. The service processing module 2033 may transmit, for example, the specific image received from the reception control module 2031 and the specific instruction completed by editing the text data read from the prompt table 2024 to the NLP system 30.

[0140] For example, the NLP system 30 may receive a specific image and a specific instruction sent from the transmission control module 2032, input them to the second multimodal generative AI model, and cause the second multimodal generative AI model to output an automatically created document (a document including content related to the image). The second multimodal generative AI model is a multimodal generative AI model provided in the NLP system 30 in place of the LLM, and is an example of a multimodal generative AI model according to one embodiment of the present disclosure.

[0141] In the third modified example, the server 20 may create an automatically created document using tags in addition to images. In this case, the server 20 may, for example, input past document information into a first multimodal generative AI model to extract images and tags. Alternatively, for example, the server 20 may input images, tags, and instruction text into a second multimodal generative AI model to create an automatically created document.

[0142] [7 Basic Computer Hardware Configuration] 13 is a block diagram showing the basic hardware configuration of a computer 90. The computer 90 includes at least a processor 91, a main memory device 92, an auxiliary memory device 93, and a communication IF (interface) 99. These components are electrically connected to one another via a bus.

[0143] The processor 91 is hardware for executing an instruction set written in a program. The processor 91 is composed of an arithmetic unit, registers, peripheral circuits, etc. The main memory device 92 is memory for temporarily storing programs and data processed by the programs, etc., and is, for example, a volatile memory such as a DRAM (Dynamic Random Access Memory). The auxiliary memory device 93 is storage for saving data and programs, and is, for example, a flash memory, an HDD (Hard Disc Drive), an optical magnetic disk, a CD-ROM, a DVD-ROM, a semiconductor memory, etc. The communication IF 99 is an interface for inputting and outputting signals for communicating with other computers via a network using wired or wireless communication standards.

[0144] A network is composed of the Internet, a LAN, various mobile communication systems constructed by wireless base stations, etc. For example, networks include 3G, 4G, and 5G mobile communication systems, LTE (Long Term Evolution), and wireless networks (e.g., Wi-Fi (registered trademark)) that can connect to the Internet via a predetermined access point. In the case of a wireless connection, communication protocols include, for example, Z-Wave (registered trademark), ZigBee (registered trademark), and Bluetooth (registered trademark). In the case of a wired connection, networks also include those that are directly connected using a USB (Universal Serial Bus) cable, etc.

[0145] It should be noted that the computer 90 can be virtually realized by distributing all or part of each hardware configuration across multiple computers 90 and interconnecting them via a network. In this way, the computer 90 is a concept that includes not only a computer in which each piece of hardware is housed in a single housing or the like, but also a virtualized computer system.

[0146] [8 Basic Functional Configuration of a Computer] The functional configuration of a computer realized by the basic hardware configuration of a computer 90 will be described. The computer performs the functions of a control unit, a storage unit, and a communication unit. Note that each function of the computer 90 can be performed by distributing all or part of the functions among multiple computers 90 connected to each other via a network. In this way, the concept of a computer 90 includes not only a single computer but also a virtualized computer system.

[0147] The memory unit is realized by the main memory device 92 and the auxiliary memory device 93. The memory unit stores data, various programs, and various databases. The control unit is realized by the processor 91 reading out various programs stored in the auxiliary memory device 93, expanding them in the main memory device 92, and executing processing in accordance with the programs. The control unit can perform various information processing functions depending on the type of program. In this way, the computer is realized as an information processing device that processes information.

[0148] The control unit can also cause the processor 91 to allocate a storage area corresponding to the storage unit in the main storage unit 92 or the auxiliary storage unit 93 in accordance with the programs. Furthermore, the control unit can cause the processor 91 to add, update, and delete data stored in the storage unit in accordance with various programs.

[0149] A database refers to a relational database, which manages data sets called tables, which are structured by rows and columns, by associating them with each other. In a database, a table is called a table, a column in a table is called a column, and a row in a table is called a record. In a relational database, relationships between tables can be set and associated.

[0150] Typically, each table constituting a database has a column set as a key for uniquely identifying a record, but setting a key to a column is not essential. The control unit can cause the processor 91 to add, update, or delete records in a specific table stored in the storage unit in accordance with various programs.

[0151] The communication unit is realized by the communication IF 99. The communication unit has the function of communicating with other computers 90 via a network. The communication unit can receive information transmitted from other computers 90 and output the information to the control unit. The control unit can cause the processor 91 to execute information processing on the received information in accordance with various programs. In addition, the communication unit can transmit information output from the control unit to other computers 90.

[0152] Although several embodiments of the present disclosure have been described above, these embodiments can be embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and modifications are intended to be included in the scope of the inventions and their equivalents as defined in the claims, as well as in the scope and spirit of the inventions.

[0153] [9. Appendix] The matters described in the above embodiments will be supplemented below.

[0154] <Appendix 1> A program to be executed by a computer having a processor and a memory, the program causing the processor to execute the following steps: analyzing multiple documents created in the past for a specified task, extracting and storing multiple tags for each task; accepting a selection of a task to which the document creation is linked; presenting multiple tags associated with the selected task; accepting specifications for the presented tags; inputting a word as the specified tag and an instruction sentence instructing the creation of a document using the word into a large-scale language model, and outputting a document using the word from the large-scale language model; and presenting the document using the output word.

[0155] <Appendix 2> In the storing step, the extracted tags are analyzed and stored in a manner according to the analysis result; The program according to claim 1, wherein the step of presenting a plurality of tags presents a plurality of tags in a presentation format according to an analysis result.

[0156] <Appendix 3> A program described in Appendix 2 that causes a processor to execute a step of analyzing the extracted multiple tags, classifying the multiple tags into hierarchies, grouping the multiple tags, or a combination of these two, and registering them.

[0157] <Appendix 4> The program according to claim 3, wherein in the registration step, hierarchical classification is performed based on a predetermined dictionary tool.

[0158] <Appendix 5> The program according to any one of (Supplementary Note 1) to (Supplementary Note 4), wherein in the storing step, a plurality of tags are extracted at a predetermined timing.

[0159] <Appendix 6> The program according to claim 5, wherein the plurality of tags are extracted each time a new document is created in a predetermined task.

[0160] <Appendix 7> A program according to (Appendix 5) that extracts multiple tags at a predetermined interval.

[0161] <Appendix 8> A program according to any one of (Appendix 1) to (Appendix 7) that causes a processor to execute a step of displaying tags related to a specified tag.

[0162] <Appendix 9> The program according to claim 8, wherein the display step displays the specified tag and a tag related to the specified tag in a linked manner.

[0163] <Appendix 10> The program according to claim 9, which causes a processor to execute a step of accepting a designation by a flick operation for a displayed tag.

[0164] <Appendix 11> A program to be executed by a computer having a processor and a memory, the program causing the processor to execute the following steps: analyzing multiple documents created in the past for a specified task, extracting and storing multiple tags for each task; accepting a selection of a task to which the document creation is linked; presenting multiple tags associated with the selected task; accepting a specification for the presented tags and a specified image, or a specification for the image; inputting the specified tags and image, or the specified image, and an instruction to create a document into a multimodal generative AI model, and causing the multimodal generative AI model to output a document including at least content related to the image; and presenting the output document.

[0165] <Appendix 12> An information processing device comprising a control unit and a storage unit, wherein the control unit executes all steps in the program according to any one of (Supplementary Note 1) to (Supplementary Note 11).

[0166] <Appendix 13> A method executed by a computer having a processor and a memory, wherein the processor executes all steps in the program described in any one of (Appendix 1) to (Appendix 11).

[0167] <Appendix 14> A system comprising means for executing all steps in the program described in any one of (Appendix 1) to (Appendix 11). [Explanation of symbols]

[0168] 1. System 10...Terminal device 120…Communications Department 13...Input device 131...Touch-sensitive devices 14...Output device 141...Display 15...Memory 16…Storage 19...Processor 20...Server 22...Communication IF 23...Input / output interface 25…Memory 26…Storage 29...Processor 30...NLP system

Claims

1. A program to be executed by a computer having a processor and a memory, the program causing the processor to: A step of analyzing a plurality of documents created in the past for a predetermined task, and extracting and storing a plurality of tags for each task; receiving a selection of the task associated with the creation of the document; presenting a plurality of the tags associated with the selected task; receiving a designation for the presented tag; a step of inputting the designated word as the tag and an instruction sentence instructing the creation of a document using the word into a large-scale language model, and outputting a document using the word from the large-scale language model; presenting a document using the outputted words; A program that executes the following.

2. In the storing step, the extracted tags are analyzed and stored in a manner according to the analysis result; The program according to claim 1 , wherein in the step of presenting a plurality of tags, the tags are presented in a presentation format according to the analysis result.

3. 3. The program according to claim 2, wherein in the storing step, the extracted tags are analyzed, and the tags are stored after being classified into hierarchies, grouped, or a combination of the two.

4. 4. The program according to claim 3, wherein the hierarchical division is performed based on a predetermined dictionary tool.

5. 2. The program according to claim 1, wherein the step of storing extracts the plurality of tags at a predetermined timing.

6. 6. The program according to claim 5, wherein the tags are extracted every time a new document is created in the predetermined task.

7. 6. The program according to claim 5, wherein the plurality of tags are extracted at a predetermined interval.

8. 2. The program product according to claim 1, wherein the program causes the processor to execute a step of displaying the tags associated with the specified tag.

9. 9. The program according to claim 8, wherein the step of displaying displays the specified tag and the tag related to the specified tag in a linked manner.

10. The program according to claim 9 , further comprising: causing the processor to execute a step of accepting a designation by a flick operation for the displayed tag.

11. A program to be executed by a computer having a processor and a memory, the program causing the processor to: A step of analyzing a plurality of documents created in the past for a predetermined task, and extracting and storing a plurality of tags for each task; receiving a selection of the task associated with the creation of the document; presenting a plurality of the tags associated with the selected task; receiving a designation for the presented tag and a predetermined image, or a designation for the image; inputting the specified tag and the image, or the specified image and an instruction for creating a document, into a multimodal generative AI model, and outputting a document including at least content related to the image from the multimodal generative AI model; presenting the output document; A program that executes the following.

12. 12. An information processing apparatus comprising: a control unit; and a storage unit, wherein the control unit executes all steps of the program according to claim 1.

13. A method implemented on a computer having a processor and a memory, wherein the processor executes all the steps of the program of any one of claims 1 to 11.

14. A system comprising means for executing all steps of the program according to any one of claims 1 to 11.

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