Program, method, information processing device, and system

Abstract

To compare information transmission in an unspecified field with information extracted from another information source.SOLUTION: A non-transitory computer-readable recording medium storing a program for operating a computer, the program causing a processor of the computer to execute: receiving designation of a text; and extracting, from an information source available to an artificial intelligence system, at least one source text including a description similar to a designated text that is the designated text. Generating a prompt including an instruction to output information about the source sentence and an instruction to compare the extracted source sentence with a specified sentence, and presenting, to a user, the information about the source sentence and a result of the comparison between the specified sentence and the source sentence, based on an answer obtained from a large scale language model provided by an artificial intelligence system by inputting the prompt to the large scale language model.SELECTED DRAWING: Figure 10

Description

[Technical Field]

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

[0002] In recent years, information has been widely disseminated, primarily via the Internet, but the information disseminated may contain information whose veracity is unknown. If false information is spread throughout society, it could lead to incorrect decisions and actions based on that information, causing social unrest.

[0003] Patent document 1 describes a post evaluation device in which a post data acquisition unit 111 requests SNS post data related to the railway line to be evaluated from an SNS server 103 and receives the SNS post data, a highly reliable information acquisition unit 112 requests highly reliable information related to delays on the railway line to be evaluated from a highly reliable information distribution server 104 and receives the highly reliable information, and an accuracy evaluation unit 123 determines whether or not there is a delay mentioned in the post by comparing it with the aggregated results of the highly reliable information and determines an accuracy index. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2022-122297 Summary of the Invention [Problem to be solved by the invention]

[0005] The technology described in Patent Document 1 is limited to specific fields in which a given information transmission can be compared with information extracted from other information sources, and therefore cannot compare information transmissions in unspecified fields with information extracted from other information sources.

[0006] The present disclosure provides a comparison of information dissemination in an unspecified field with information extracted from other sources. [Means for solving the problem]

[0007] A program for operating a computer, the program causing a processor of the computer to execute the following steps: accepting the specification of a sentence; extracting at least one source sentence containing a description similar to the specified sentence from an information source available to the artificial intelligence system, generating a prompt including instructions to output information about the source sentence and instructions to compare the extracted source sentence with the specified sentence; and presenting to a user information about the source sentence and the comparison result between the specified sentence and the source sentence based on an answer obtained from a large-scale language model provided by the artificial intelligence system by inputting the prompt into the large-scale language model. [Effects of the Invention]

[0008] According to the present disclosure, information disseminated in an unspecified field can be compared with information extracted from other information sources. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 2 is a block diagram showing the functional configuration of the system 1. [Figure 2] 2 is a block diagram showing the functional configuration of the terminal device 10. FIG. [Figure 3] FIG. 2 is a block diagram showing the functional configuration of the server 20. [Figure 4] FIG. 2 is a diagram showing the data structure of a user table 2021. [Figure 5] FIG. 2 shows the data structure of an information source table 2022. [Figure 6] FIG. 10 is a diagram showing the data structure of a prompt information table 2023. [Figure 7] FIG. 10 is a diagram showing the data structure of a response information table 2024. [Figure 8] 10 is a flowchart of a sentence comparison process according to the present embodiment. [Figure 9] FIG. 10 is a schematic diagram showing an example of a reception screen D1 for a specified sentence. [Figure 10] FIG. 10 is a schematic diagram showing an example of a first results screen D2. [Figure 11] FIG. 10 is a schematic diagram showing an example of a second results screen D3. [Figure 12] 10 is a flowchart of a modified example of the sentence comparison process. [Figure 13] FIG. 10 is a schematic diagram showing an example of an extraction result screen D4. [Figure 14] FIG. 10 is a schematic diagram showing an example of a comparison result screen D5. [Figure 15] FIG. 2 is a block diagram showing the basic hardware configuration of a computer 90. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. In the drawings for explaining the embodiment, the same components are generally designated by the same reference numerals, and repeated description thereof will be omitted.

[0011] <1 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 artificial intelligence system 40. The terminal device 10, the server 20, and the artificial intelligence system 40 are communicatively connected via, for example, a network 80.

[0012] 1, the number of terminal devices 10 included in the system 1 is not limited to one. The number of terminal devices 10 included in the system 1 may be two or more.

[0013] 1 shows an example in which the system 1 includes one server 20, but the number of servers 20 included in the system 1 is not limited to one. The server 20 may be composed of multiple servers depending on the functions it has. Furthermore, the server 20 may be, for example, a collection of multiple devices. The way in which the multiple functions required to realize the server 20 according to this embodiment are allocated to one or multiple pieces of hardware can be determined appropriately in consideration of the processing capacity of each piece of hardware and / or the specifications required for the server 20.

[0014] 1 is realized by, for example, a mobile terminal such as a smartphone or tablet compatible with a mobile communication system. Alternatively, the terminal device 10 may be realized by, for example, a stationary personal computer (PC) or a laptop PC. Furthermore, the terminal device 10 may be realized by, for example, a wearable terminal such as a head mounted display (HMD).

[0015] 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 (e.g., a touch panel, a touch pad, etc.) for receiving input operations from a user. The output device 14 is a device (e.g., a display, a speaker, etc.) for presenting information to a user.

[0016] The server 20 is realized by, for example, an information processing device 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 presenting information to the user.

[0017] The artificial intelligence system 40 is realized by, for example, one or more information processing devices connected to the network 80. The artificial intelligence system 40 may be configured as a part of the server 20.

[0018] Each information processing device is configured by a computer equipped with an arithmetic unit and a storage device. The basic hardware configuration of the computer and the basic functional configuration of the computer realized by the hardware configuration will be described later. For each of the terminal device 10, the server 20, and the artificial intelligence system 40, explanations that overlap with the basic hardware configuration and basic functional configuration of the computer will be omitted.

[0019] <Configuration of terminal device> Fig. 2 is a block diagram showing an example 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, an audio processing unit 17, a microphone 171, a speaker 172, 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 or the like.

[0020] 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 the signal generated by the control unit 190 and transmits it to the outside (for example, the server 20). The communication unit 120 performs reception processing on the signal received from the outside and outputs it to the control unit 190.

[0021] The input device 13 is a device for inputting instructions or information by a user operating the terminal device 10. The input device 13 is realized, for example, by a touch-sensitive device 131 or the like, which inputs instructions by touching an operation surface. When 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 the electrical signals 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.

[0022] 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 or the like. The display 141 displays data 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 or the like.

[0023] The audio processing unit 17 performs, for example, digital-to-analog conversion processing of an audio signal. The audio processing unit 17 converts a signal provided from the microphone 171 into a digital signal and provides the converted signal to the control unit 190. The audio processing unit 17 also provides the audio signal to the speaker 172. The audio processing unit 17 is realized, for example, by a processor for audio processing. The microphone 171 receives audio input and provides an audio signal corresponding to the audio input to the audio processing unit 17. The speaker 172 converts the audio signal provided from the audio processing unit 17 into audio and outputs the audio to the outside of the terminal device 10.

[0024] The storage unit 180 is realized by, for example, the memory 15, the storage 16, etc., and stores data and programs used by the terminal device 10. The storage unit 180 stores, for example, user information 181.

[0025] User information 181 stores information about the operating user, including, for example, the user ID, name, age, address, date of birth, and date of registration for the service.

[0026] 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 functions as an operation reception unit 191, a transmission / reception unit 192, and a presentation control unit 193 by operating in accordance with the program.

[0027] The operation reception unit 191 performs processing for receiving instructions or information input from the input device 13. For example, the operation reception unit 191 receives instructions or information input from the touch-sensitive device 131 or the like.

[0028] Furthermore, the operation reception unit 191 receives audio information input from the microphone 171. Specifically, for example, the operation reception unit 191 receives audio data that is input from the microphone 171 and converted into digital data by the audio processing unit 17.

[0029] The transmitting / receiving 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, for example, the transmitting / receiving unit 192 transmits instructions input by a user to the server 20. The transmitting / receiving unit 192 receives information provided by the server 20.

[0030] The presentation control unit 193 controls the output device 14 and the like to present information such as information provided by the server 20 to the user.

[0031] <Server functional configuration> 3 is a diagram showing an example of the functional configuration of the server 20. As shown in FIG. 3, the server 20 functions as a communication unit 201, a storage unit 202, and a control unit 203.

[0032] The communication unit 201 performs processing for the server 20 to communicate with external devices.

[0033] The storage unit 202 includes, for example, a user table 2021, an information source table 2022, a prompt information table 2023, a response information table 2024, a prompt template 2028, and the like.

[0034] The user table 2021 is a table that stores information about users who register with the service of the present disclosure.

[0035] The information source table 2022 is a table that stores information regarding information sources that can be obtained via the network 80 (e.g., databases of papers and magazine articles, electronic journals, news media, public institutions, etc., including any information source that disseminates information via the network 80).

[0036] The prompt information table 2023 is a table that stores prompt information, which is information related to prompts. Specifically, for example, the prompt information is input data to be embedded in each field of a prompt template 2028, which will be described later.

[0037] The response information table 2024 is a table that stores response information, which is information about responses that the large-scale language model of the artificial intelligence system 40 outputs in response to input of a prompt.

[0038] The prompt template 2028 is template data for a prompt that has a field for embedding specified input data. That is, by inputting predetermined input data into the prompt template 2028, a prompt to be input to the large-scale language model is generated. The prompt template 2028 is, for example, text data. The prompt template 2028 is, for example, a combination of at least one of instructions 2028a, 2028b, 2028c, 2028d, and 2028e, which are sentences indicating the respective instructions. Note that in the present disclosure, when sentences included in instructions 2028a to 2028e are used to create a prompt, it is not necessary to combine all of the sentences included in instructions 2028a to 2028e; some or multiple parts of the sentences of instructions 2028a to 2028e may be combined. In the following example, the fields for embedding input data are indicated by the portions enclosed in curly brackets.

[0039] As a first example, instructions 2028a include instructions for the artificial intelligence system to extract at least one source sentence containing a description similar to the specified sentence from available information sources and output information about the source sentence.

[0040] (Example 1 of Instruction 2028a) Extract at least one source sentence that contains a description similar to the specified #Specified sentence from the information sources available to you, and output the information according to the #Information about the source sentence item. #specified text {specified text} #Information about the source text -Original title Access to the source document (URL) - Name and reliability of the source of information The date the source article was published · The body of the source text

[0041] As a second example, the instruction 2028a includes an instruction to extract at least one source sentence that includes a description similar to the specified sentence from a pre-specified information source, and to output information about the source sentence.

[0042] (Second example of Instruction 2028a) Extract at least one source sentence that contains a description similar to the specified #specified sentence from one of the specified #information sources, and output the information according to the #information about the source sentence item. #specified text {specified text} #Source (Source 1) Source Name: {Source Name} Source URL: {Access} · Trust level: {trust level} (Source 2) Source Name:.... #Information about the source text -Original title Access to the source document (URL) - Name and reliability of the source of information The date the source article was published · The body of the source text

[0043] As a third example, instruction 2028a includes an instruction to acquire text from a specified webpage as the designated text from information for identifying the specified webpage (webpage identification information such as a URL). In this case, the webpage is, for example, a webpage that includes text data, image data including text, etc., such as a webpage assigned to an individual post on a social networking service (SNS). Furthermore, the text from the webpage is, for example, text that is displayed on a terminal when the user accesses the webpage. Thus, for example, artificial intelligence system 40 accesses the information for identifying the webpage and acquires the text from the webpage as the designated text.

[0044] (Example 3 of Instruction 2028a) Using a post posted on the specified #SNS post as the specified sentence, extract at least one source sentence from one of the specified #information sources that contains a description similar to the specified sentence, and output the information according to the #information about source sentence item. #SNSPost {SNS post URL} #Source (Source 1) Source Name: {Source Name} Source URL: {Access} · Trust level: {trust level} (Source 2) Source Name:.... #Information about the source text -Original title Access to the source document (URL) - Name and reliability of the source of information The date the source article was published · The body of the source text

[0045] The instructions 2028b include, for example, an instruction to compare the extracted source sentence with a specified sentence. - Instruction to output the degree of match between the source sentence and the specified sentence - Instruction to output the basis for determining the degree of match Instruction to output at least one of information about matching parts and information about different parts between the specified sentence and the source sentence

[0046] (Example of Instruction 2028b) Compare the extracted source text with the specified text and output the information according to the #Information about the comparison results item. #Information about comparison results - Matching parts of the specified sentence and the source sentence Differences between the specified text and the source text - Matching of the specified sentence with the source sentence · Basis for determining the degree of match

[0047] In addition to the above examples, the instruction 2028b may include an instruction to compare the source sentence with the specified sentence while placing emphasis on at least one specific viewpoint. The specific viewpoint may be, for example, at least one of the viewpoints related to each item in the "Viewpoint" field of the information source table 2022, or may be a viewpoint different from the viewpoints related to each item in the "Viewpoint" field of the information source table 2022. The viewpoint items in the instruction 2028b are, for example, predetermined by the provider of the service of the present disclosure.

[0048] (Additional example of Instruction 2028b) When comparing the source text with the specified text, please pay attention to the following points: #perspective Point 1: Clarity of source ·Perspective 2: Information Transparency

[0049] Instruction 2028c includes an instruction to output a credibility indicating the degree of credibility of the specified sentence based on the comparison result and the reliability of the information source of the source sentence. For example, instruction 2028c includes an instruction to output the credibility by performing an arbitrary calculation based on the degree of match specified in instruction 2028b and the reliability presented in instruction 2028a. Note that the credibility may be calculated by server 20 using an arbitrary method such as the following calculation formula:

[0050] (Example of Instruction 2028c) Determine the credibility using the formula. If multiple source sentences are compared to the specified sentence, the Source Credibility should be the average of the source credibility scores for each source sentence compared to the specified sentence. #calculation formula [Credibility] = [Agreement] * [Source credibility] / 100

[0051] When multiple source sentences are extracted, instruction 2028d includes an instruction to select at least one source sentence from the multiple source sentences based on the reliability of the information source from which the source sentences were extracted, and compare it with the specified sentence. For example, when multiple source sentences are extracted, instruction 2028d includes an instruction to select a source sentence under the following example conditions, and compare it with the specified sentence. Select a predetermined number of source sentences in order of reliability Select all source sentences whose source reliability is equal to or greater than a given value.

[0052] (Example of Instruction 2028d) If multiple source sentences can be extracted, select the three most reliable source sentences and compare each of them with the specified sentence.

[0053] As a first example, instruction 2028e includes an instruction to determine the reliability of the information source of the source sentence based on at least one specific viewpoint. The specific viewpoint may be, for example, at least one of the viewpoints related to each item in the "Viewpoint" field of information source table 2022, or a viewpoint different from the viewpoints related to each item in the "Viewpoint" field of information source table 2022. Note that when instruction 2028e is included in prompt template 2028, the reliability of the information source is output from a large-scale language model. Therefore, in this case, prompt template 2028 does not need to include information related to the reliability of each information source as shown in the second example of instruction 2028a. The viewpoint items in instruction 2028e are, for example, predetermined by the provider of the service of the present disclosure.

[0054] (Example 1 of Instruction 2028e) Once you have extracted the source text, determine the reliability of the source of that text by scoring it on a scale of 0 to 100 for each of the following #perspectives, and averaging the scores for each perspective. #perspective Point 1: Clarity of source ·Perspective 2: Information Transparency Perspective 3: Political bias Point 4: Appropriateness of the reporting format ...

[0055] As a second example, the instructions 2028e may include instructions to determine the reliability of the source sentence based on at least one specific viewpoint. For example, the instructions 2028e may include instructions to determine the reliability of the source sentence by analyzing the description of the source sentence itself from a specific viewpoint.

[0056] (Second example of Instruction 2028e) After extracting the source text, determine its reliability by analyzing it from the following #perspectives. Score the source text for each #perspective on a scale of 0 to 100, and then average the scores for each perspective to determine the reliability of the source text. #perspective Point 1: Clarity of source ·Perspective 2: Information Transparency Perspective 3: Political bias Point 4: Appropriateness of the reporting format ...

[0057] Furthermore, the answer data from the large-scale language model is preferably in a format structured for each item, such as a JSON string. This makes it possible to easily extract text data for each item to be extracted from the answer data output from the large-scale language model in response to an input prompt. Therefore, the prompt template 2028 preferably includes an instruction to structure the answer for each item. This makes it possible to obtain answer data from the large-scale language model in a format structured for each item.

[0058] 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. By operating in accordance with the program, the control unit 203 fulfills the functions of a reception control module 2031, a transmission control module 2032, a prompt generation module 2033, a data analysis module 2034, and a presentation module 2035.

[0059] The reception control module 2031 controls the process of the server 20 receiving signals from external devices in accordance with a communication protocol. Specifically, for example, the reception control module 2031 receives signals transmitted from the terminal device 10 and signals transmitted from the artificial intelligence system 40.

[0060] The transmission control module 2032 controls the process in which the server 20 transmits signals to external devices in accordance with a communication protocol. Specifically, for example, the transmission control module 2032 transmits, to the terminal device 10, information about various UIs (described later) to be displayed on the display 141 of the terminal device 10. Also, for example, the transmission control module 2032 transmits a request including a prompt to the artificial intelligence system 40.

[0061] The prompt generation module 2033 generates a prompt to be input to the large-scale language model of the artificial intelligence system 40. Specifically, the prompt is generated by inputting information received from the user into a predetermined field of the prompt template 2028. For example, the prompt generation module 2033 generates a prompt by inputting information obtained from each item in the information source table 2022 and the prompt information table 2023 into the field of each item in the prompt template 2028.

[0062] For example, the prompt generation module 2033 generates a prompt by entering the following information into each field of the prompt template 2028: {Specified text}: Information contained in the "Specified text" item in the prompt information table 2023 {Source Name}: Information contained in the "Source Name" item in Source Table 2022 {Access destination}: Information contained in the "Access destination" item in the information source table 2022 {Reliability}: Information contained in the "Reliability" item in the Source Table 2022 {SNS Post URL}: Information received from the user to identify the specified web page (web page identification information such as URL)

[0063] The data analysis module 2034 analyzes the response data output from the large-scale language model and controls the process of extracting necessary information. Specifically, the data analysis module 2034 extracts, from the response data, information about the source sentence and information about the comparison result between the specified sentence and the source sentence.

[0064] For example, as described above, accepting answer data in a structured format such as JSON makes it easier to analyze the answer data. The data analysis module 2034 divides the structured answer data into items and obtains information corresponding to each item from the answer data to generate a result UI (described later). Even if the answer data is not structured, the data analysis module 2034 can extract text data for any item from the answer data by using any natural language processing technology or the like.

[0065] In addition, when multiple source sentences are output from a large-scale language model (when the answer data includes information about multiple source sentences), the data analysis module 2034 may select a predetermined number of source sentences from the multiple source sentences based on predetermined criteria, and extract information about the selected source sentences and information about the comparison results between the source sentences and the specified sentence from the answer data.

[0066] The predetermined criteria may include, for example, a criterion regarding the reliability of the information source of the source sentence and / or a criterion regarding the degree of similarity between the source sentence and the specified sentence. When multiple criteria are combined, one of the criteria may be applied preferentially.

[0067] For example, based on the criteria regarding the reliability value of the information source of the source sentence, the data analysis module 2034 selects the source sentence as follows, for example: Select a predetermined number of source sentences in order of reliability Select all source sentences whose source reliability is equal to or greater than a given value.

[0068] For example, based on the criteria regarding the degree of similarity between the source sentence and the specified sentence, the data analysis module 2034 selects the source sentence as follows: -Select a predetermined number of source sentences in order of their highest match with the specified sentence Select all source sentences that match the specified sentence to a given value or more.

[0069] Furthermore, when multiple source sentences are output from the large-scale language model, the data analysis module 2034 may sort the response data for each source sentence in an order based on a predetermined criterion, and display information about the source sentence and the comparison results between the specified sentence and the source sentence in the sorted order in a result UI (described later). The predetermined criterion may include at least one of a criterion related to the reliability value of the information source of the source sentence and a criterion related to the degree of similarity between the source sentence and the specified sentence. When multiple criteria are combined, one of the criteria may be applied preferentially.

[0070] For example, based on the criteria related to the reliability value of the information source of the source sentence, the data analysis module 2034 sorts the answer data as follows, for example: -Sort the response data for each source sentence in descending order of reliability of the source

[0071] For example, based on the criteria related to the degree of similarity between the source sentence and the specified sentence, the data analysis module 2034 rearranges the response data as follows: -Sort the response data for each source sentence in order of the degree of match with the specified sentence.

[0072] The presentation module 2035 presents various UIs to the user. For example, the presentation module 2035 presents various UIs, etc., described below, to the user.

[0073] <Functional configuration of artificial intelligence system 40> The artificial intelligence system 40 is a system that includes at least one information processing device and outputs a response to a request that has been received as an input.

[0074] The artificial intelligence system 40 is, for example, a large-scale language model system (LLM system) that performs natural language processing. For example, when the server 20 or the like sends a prompt to the large-scale language model of the artificial intelligence system 40, the artificial intelligence system 40 sends data including text data to the server 20 or the like in response to the prompt. The artificial intelligence system 40 may also be a generative AI system that generates image data (including still images and videos) and audio data. For example, when the server 20 or the like sends a prompt to the model of the artificial intelligence system 40, the artificial intelligence system 40 sends data including image data and audio data to the server 20 or the like in response to the prompt. The artificial intelligence system 40 may also be a system that can process multiple types of data, such as text, images, audio, and videos, all at once. Examples of the artificial intelligence system 40 include ChatGPT, Perplexity, Copilot, Gemini, Midjourney, Stable Diffusion, and Sora. The artificial intelligence system 40 may also be an artificial intelligence system provided by the operator of the server 20.

[0075] In this embodiment, the artificial intelligence system 40 will be described as an example of a system that handles a large-scale language model. In this embodiment, a request to the artificial intelligence system 40 includes prompt text data to be input into the large-scale language model, and a response from the artificial intelligence system 40 includes answer data output from the large-scale language model.

[0076] <2 Data Structure> 4 to 7 are diagrams showing examples of data structures of information stored in the server 20. Note that FIGS. 4 to 7 are merely examples and do not exclude data not shown.

[0077] 4 is a diagram showing the data structure of the user table 2021. The user table 2021 is a table having a user ID as a primary key and columns such as a user name.

[0078] The item "user ID" is an item for storing a user ID that identifies a user.

[0079] The item "user name" is an item for storing the name of the user. The user name may be set to any character string such as the user's name or nickname.

[0080] 5 is a diagram showing the data structure of the information source table 2022. The information source table 2022 is a table having an information source ID as a primary key and columns such as information source name, access destination, viewpoint, and reliability.

[0081] The item "information source ID" is an item for storing an information source ID that identifies an information source.

[0082] The item "information source name" is an item for storing the name of the information source. The information source name may include any character string information, such as the name of the information provider (e.g., a public institution or news media), the name of a website, the name of a journal or magazine, or the name of a publication.

[0083] The item "access destination" is an item that stores a link destination for accessing an information source. For example, the item "access destination" stores a character string that indicates a URL for accessing the website of the information source.

[0084] The item "perspective" is an item that stores information about the evaluation of an information source from a predetermined perspective. As shown in FIG. 5, the information source table 2022 stores information about the evaluation of an information source from at least one perspective, such as "perspective 1," "perspective 2," etc., as items related to the item "perspective." Specifically, the item "perspective" stores a numerical value that indicates the degree of evaluation of an information source from a predetermined perspective. For example, the higher the evaluation for each perspective, the larger the numerical value stored in the item "perspective."

[0085] Furthermore, the predetermined viewpoints whose evaluations are stored in the "viewpoint" item specifically include viewpoints for determining the reliability of information sources. For example, the predetermined viewpoints include the following viewpoints. That is, "Viewpoint 1," "Viewpoint 2," etc. in FIG. 5 can be read as, for example, "Clarity of source," "Transparency of information," etc. Clarity: clarity of source, transparency of information, etc. Accuracy: accuracy of information, consistency of information, date and time of information release and frequency of updates, etc. · Objectivity perspective: objectivity of information, fairness (political bias, etc.), etc. · Expertise: the source's expertise, the author's research and writing skills, the source's history, authority, track record, etc.

[0086] The "reliability" item is an item that stores information about the reliability of an information source. Specifically, the reliability of an information source is stored as a numerical value in the "reliability" item. For example, the higher the reliability, the larger the numerical value stored in the "reliability" item. The reliability may be ranked into "high," "medium," "low," etc., depending on the reliability numerical value.

[0087] The reliability may be determined based on an evaluation of each perspective of the information source. For example, the numerical value stored in the "reliability" item may be determined based on the numerical value stored in each item of the "perspective" item. For example, the numerical value of the "reliability" item may be determined by performing any calculation (sum, average, etc.) on the numerical values ​​of each item of the "perspective" item.

[0088] Furthermore, the reliability may be determined in advance for each information source by a provider of the service of the present disclosure, etc., instead of depending on the numerical value stored in the item "perspective." In this case, the information source table 2022 may not have the item "perspective."

[0089] 6 is a diagram showing the data structure of the prompt information table 2023. The prompt information table 2023 is a table having a prompt information ID as a primary key and columns such as a user ID and a specified sentence.

[0090] The item "prompt information ID" is an item for storing a prompt information ID that identifies prompt information. Prompt information is information that is combined with a prompt template to generate a prompt.

[0091] The item "user ID" is an item for storing the user ID of the user who sent the prompt information.

[0092] The item "designated sentence" is an item that stores information about the designated sentence, which is a sentence designated by the user. For example, the item "designated sentence" stores text data of a sentence input by the user via the terminal device 10, or text data of a sentence acquired by the server 20 based on information input by the user for identifying the designated sentence (for example, identification information of an SNS post related to the designated sentence, identification information of a webpage on which the designated sentence is written, etc.).

[0093] The item "information source ID" is an item for storing the information source ID of the information source specified when extracting the source sentence in the prompt. The item "information source ID" may store one or more information source IDs.

[0094] 7 is a diagram showing the data structure of the response information table 2024. The response information table 2024 is a table having columns such as prompt information ID and response information, with the response information ID as the primary key.

[0095] The item "Response Information ID" is an item for storing a response information ID that identifies the response information sent from the artificial intelligence system 40 in response to the prompt.

[0096] The "prompt information ID" item is an item that stores the prompt information ID of the prompt information used to generate the prompt corresponding to the response information. Specifically, the "prompt information ID" item stores the prompt information ID of the prompt information used to generate the prompt that the server 20 sent to the artificial intelligence system 40 in order to receive the response information identified by the response information ID. For example, if the server 20 sends a prompt generated using prompt information with prompt information ID: P001 to the artificial intelligence system 40, and response information with response information ID: RP001 is output from the artificial intelligence system 40, P001 will be stored as the prompt information ID in the record whose response information ID is RP001.

[0097] The item "Response Information" is an item that stores response information output from the artificial intelligence system 40. Specifically, the item "Response Information" stores data related to the response output by the artificial intelligence system 40 in response to a received request. For example, the item "Response Information" stores data in a format according to the type of artificial intelligence system 40 (text data, image data, audio data, etc.).

[0098] <3 operations> The sentence comparison process of this embodiment will be described. The sentence comparison process is a process in which a request including a prompt, which is generated based on a specified sentence specified by a user and includes an instruction to extract a source sentence similar to the specified sentence and an instruction to compare the specified sentence with the source sentence, is sent to the artificial intelligence system 40, and the comparison result between the specified sentence and the source sentence based on the response information obtained from the artificial intelligence system 40 is presented to the user. Figure 8 is a flowchart of the sentence comparison process of this embodiment.

[0099] First, the terminal device 10 executes an application for extracting a source sentence and comparing the specified sentence with the source sentence. The extraction of the source sentence and the comparison of the specified sentence with the source sentence may be executed via a web browser. For example, a user operates the terminal device 10 to select an application and have the terminal device 10 execute the application. When the terminal device 10 executes the application, the control unit 190 displays a login screen for authenticating the user on the display 141.

[0100] The user inputs, for example, a user ID and a password on the login screen. Note that the information input by the user on the login screen is not limited to a user ID and a password, and the user may log in by inputting biometric information or the like.

[0101] In step S11, the server 20 accepts access from the terminal device 10 and authenticates the user by accepting a user ID and password.

[0102] The server 20 presents a reception UI for the specified sentence to the user via the terminal device 10. Specifically, for example, the server 20 generates a reception UI for the specified sentence based on information about the information source stored in the information source table 2022, and displays a reception screen for the specified sentence on the display 141 of the terminal device 10.

[0103] 9 is a schematic diagram showing an example of a designated sentence reception screen D1. The designated sentence reception screen D1 includes an operation object D11, an operation object D12, an operation object D13, a display object D14, and an operation object D15.

[0104] The operation object D11 accepts an operation for inputting a specified sentence. The operation object D11 accepts input of specified sentences from the user, for example, by accepting input of text data from the user.

[0105] The operation object D13 accepts an operation to input a designation of an information source to be searched for a source sentence. For example, when the operation object D13 accepts an operation from a user, the operation object D13 displays a list of information source names stored in the information source table 2022 in a selectable manner on the designated sentence reception screen D1. The terminal device 10 accepts the designation of an information source to be searched for a source sentence by accepting the selection of each object indicating an information source name from the user. The objects indicating the information source names may be divided into groups according to the reliability numerical value, such as "high reliability," "medium reliability," and "low reliability," based on a predetermined criterion regarding the reliability numerical value of the information source, and each group may be selectable collectively.

[0106] Note that the operation object D13 does not have to be provided, and in that case, at least one information source predetermined by the provider of the service of the present disclosure is specified as the source from which the source sentence is extracted. For example, an information source with a "high" reliability in the information source table 2022 may be specified as the extraction source.

[0107] The display object D14 displays the specified information source. For example, the display object D14 displays a list of information sources whose designation has been accepted by the terminal device 10 when the operation object D13 accepts an operation from the user.

[0108] The operation object D15 receives an input operation from the user instructing the extraction of a source sentence for a specified sentence and the comparison of the specified sentence with the source sentence. When the operation object D15 receives the input operation from the user, the terminal device 10 transmits to the server 20 information acquired by the input operation to the operation objects D11 and D13, as well as an instruction to generate a prompt and transmit the prompt to the artificial intelligence system 40.

[0109] In step S12, the server 20 accepts the specification of a sentence and a designation of an information source, as well as instructions to generate a prompt and send a request to the artificial intelligence system 40. Specifically, the server 20 accepts information about the specified sentence and the specified information source from the terminal device 10 based on the operation accepted by the user at the acceptance UI for the specified sentence presented in step S11. The information about the specified sentence and the information about the specified information source are examples of prompt information in this embodiment.

[0110] The server 20 stores the prompt information received from the terminal device 10 in the prompt information table 2023. Specifically, for example, the following information is stored in each item of a new record in the prompt information table 2023. Prompt Information ID: The newly assigned prompt information ID User ID: User ID accepted in step S11 · Specified sentence: Text data of the specified sentence received Source ID: The source ID of the source that accepted the designation

[0111] The server 20 searches the information source table 2022 based on the information source ID stored in the prompt information table 2023, and obtains information on the items "information source name," "access destination," and "reliability" of the corresponding record.

[0112] In step S13, the server 20 generates a prompt including an instruction to extract at least one source sentence containing a description similar to the designated sentence from an information source available to the artificial intelligence system, and an instruction to compare the extracted source sentence with the designated sentence. Specifically, the server 20 calls up the prompt template 2028 stored in the memory unit 202, and enters the prompt information stored in the prompt information table 2023 into each corresponding field in the prompt template 2028, thereby generating a prompt to be sent to the artificial intelligence system 40.

[0113] For example, the prompt generation module 2033 generates a prompt by inputting the following information into each field of the prompt template 2028: {Specified Sentence}: Information stored in the "Specified Sentence" item of the prompt information table 2023 in step S12 {Source name}: Information obtained from the item "Source name" of the source table 2022 in step S12 {Access destination}: Information obtained from the item "Access destination" of the information source table 2022 in step S12 {Reliability}: Information obtained from the item "Reliability" of the information source table 2022 in step S12

[0114] In step S14, the server 20 inputs the generated prompt into a large-scale language model provided by the artificial intelligence system 40. Specifically, for example, the server 20 transmits a request including the text data of the prompt generated in step S13 and necessary parameters (e.g., a specified number of tokens) to an API endpoint of the artificial intelligence system 40.

[0115] When the artificial intelligence system 40 receives a request from the server 20, it transmits response information, which is a response to the request, to the server 20 via the API endpoint.

[0116] In step S15, the server 20 receives the response information sent from the artificial intelligence system 40. The response information includes text data (answer data) from a large-scale language model in response to a prompt included in the request sent by the server 20. The server 20 stores the response information in the memory unit 202. Specifically, for example, in a new record in the response information table 2024, the prompt information ID numbered in step S12 is stored in the item "prompt information ID," and the response information received from the artificial intelligence system 40 is stored in the item "response information."

[0117] In step S16, the server 20 extracts necessary data from the acquired response information. Specifically, for example, the server 20 extracts information about the extracted source sentence and information about the comparison result between the specified sentence and the source sentence from the response data. The information about the source sentence is, for example, the following information: The title of the source text (the title of the web page or article where the source text was published) The source from which the source text was extracted · Source reliability - The source of the source text (web page access destination, etc.) - Publication time of the source document (date, time, etc.) · The body of the source text The information relating to the comparison result between the specified sentence and the source sentence is, for example, the information below. - Matching parts of the specified sentence and the source sentence Differences between the specified text and the source text - Matching of the specified sentence with the source sentence · Basis for determining the degree of match Comments on the comparison results

[0118] When multiple source sentences are extracted from the answer data, the server 20 may use the data analysis module 2034 to select a predetermined number of source sentences from the multiple source sentences based on predetermined criteria, and extract information about the selected source sentences and information about the comparison results between the source sentences and the specified sentence from the answer data. Alternatively, the answer data for each source sentence may be rearranged in an order based on predetermined criteria.

[0119] The server 20 generates a result UI for presenting to the user information about the source sentence and information about the comparison result between the specified sentence and the source sentence based on the information about each item extracted from the answer data. Specifically, for example, the server 20 generates a result UI according to the answer data by inputting the information about each item extracted from the answer data into fields provided in the result UI corresponding to each item.

[0120] In step S17, the server 20 presents the information about the source sentence and the comparison result between the specified sentence and the source sentence to the user. Specifically, the server 20 presents the result UI generated in step S16 to the user via the terminal device 10. For example, the server 20 causes the display 141 of the terminal device 10 to display the result screen.

[0121] 10 is a schematic diagram showing an example of the first result screen D2. As shown in FIG. 10, the first result screen D2 displays a display object D21 and a display object D22 for each extracted source sentence.

[0122] The display object D21 displays information about the source text. Specifically, the display object D21 displays, for example, the following information: The title of the source text (the title of the web page or article where the source text was published) The source from which the source text was extracted · Source reliability - The source of the source text (web page access destination, etc.) - Publication time of the source document (date, time, etc.) · The body of the source text

[0123] The display object D22 displays information about the comparison result between the specified sentence and the source sentence. Specifically, the display object D22 displays information about the following, for example: - Matching parts of the specified sentence and the source sentence Differences between the specified text and the source text - Matching of the specified sentence with the source sentence · Basis for determining the degree of match Comments on the comparison results

[0124] In step S16, if the data analysis module 2034 has extracted information relating to a predetermined number of source sentences from the answer data, the first result screen D2 displays, using display objects D21 and D22, only the information relating to the source sentences selected by the data analysis module 2034. On the other hand, information relating to source sentences not selected by the data analysis module 2034 is not displayed.

[0125] Also, in step S16, if the data analysis module 2034 rearranges the information of the source sentences included in the response data in a predetermined order, the first result screen D2 displays the display objects D21 and D22 related to each source sentence in that order.

[0126] Fig. 11 is a schematic diagram showing an example of the second result screen D3. As shown in Fig. 11, the second result screen D3 includes a display object D31 and operation objects D331 to D333.

[0127] The display object D31 displays information about the credibility of the specified text. Specifically, for example, the display object D31 displays the following information: Credibility score Comments on the credibility of the specified text, such as the basis for determining the credibility or the results of comparing the specified text with a given source text.

[0128] The operation objects D331 to D333 accept an operation for inputting a specification of a question for the information presented to the user. For example, when the operation objects D331 to D333 accept an input operation from the user, the terminal device 10 transmits to the server 20 a request to input a question regarding the character string displayed on the object that accepted the operation into the large-scale language model. The server 20 generates a prompt including the question accepted from the terminal device 10 and inputs it into the large-scale language model of the artificial intelligence system 40. When the server 20 receives a response from the artificial intelligence system 40, it extracts answer data included in the response and presents it to the user via the terminal device 10.

[0129] 11, the operation object D331 displays a question about the content of the specified sentence, for example, a specific description included in the specified sentence. For example, by inputting an operation to the operation object D331, the server 20 generates a prompt including an instruction to explain the details of the description based on the description in the source sentence, and inputs the generated prompt into the large-scale language model, thereby obtaining an answer to the user's question from the large-scale language model.

[0130] 11, the operation object D332 displays a question regarding supplemental information for the specified sentence. For example, by inputting an operation to the operation object D332, the server 20 generates a prompt including an instruction to present supplemental information for the specified sentence, for example, information that is not stated in the specified sentence but is stated in the source sentence, and inputs the generated prompt into the large-scale language model, thereby obtaining an answer to the user's question from the large-scale language model.

[0131] 11, the operation object D333 displays a question regarding the content of the source sentence. For example, by inputting an operation to the operation object D333, the server 20 generates a prompt including an instruction to provide a commentary, summary, explanation, etc. of the source sentence, and inputs the generated prompt into the large-scale language model, thereby obtaining an answer to the user's question from the large-scale language model.

[0132] Additionally, the server 20 may display, on the first result screen D2 and the second result screen D3, objects for inputting evaluations (feedback) regarding information on the source sentence presented to the user and information on the comparison result between the specified sentence and the source sentence. For example, an object for receiving a user's evaluation of the information displayed in each object may be displayed near at least one of the display objects D21, D22, and D31. The object may receive a user's evaluation in a selective manner, such as "good" or "bad." The terminal device 10 receives information regarding the user's evaluation of each piece of information by accepting an operation on the object and transmits it to the server 20. The server 20 receives information regarding the user's evaluation and stores it in the storage unit 202. The server 20 transmits response data related to the information presented to the user and information regarding the user's evaluation to the artificial intelligence system 40. This allows the user's evaluation of the response data to be used for training a large-scale language model or for the operator of the artificial intelligence system 40 to improve the artificial intelligence system 40.

[0133] <Modification> Each step of the above-described sentence comparison process can be executed by either the terminal device 10 or the server 20. In the above description, an example in which each step is executed in a specific order is shown, but the execution order of each step is not limited to the example described above as long as there is no dependency between the steps.

[0134] In the above embodiment, the server 20 accepts information about the specified sentence from the user by presenting the specified sentence acceptance screen D1 to the user, and presents information about the source sentence and information about the comparison result between the specified sentence and the source sentence by presenting the first result screen D2 and the second result screen D3 to the user. However, the server 20 may execute each step of the sentence comparison process while the web page containing the specified sentence is displayed on the display 141 of the terminal device 10.

[0135] For example, an application for the sentence comparison process is executed in advance on the terminal device 10. In response to a user operation, the terminal device 10 starts a web browser or the like, accesses a web page on which the specified sentence is posted, and displays the specified sentence on the display 141.

[0136] For example, when a user operates terminal device 10 to select a range of text displayed on display 141 by a web browser application, terminal device 10 may transmit text data of the selected range to server 20, regarding the designated text as being designated. Server 20 may execute the processes from step S12 of the text comparison process onward based on the text data of the designated text transmitted from terminal device 10. In this case, information about the source text and information about the comparison result between the designated text and the source text presented to the user may be presented to the user by, for example, a pop-up display or an overlay display on the screen of the web browser application or the like that displayed the designated text. This allows the user to easily compare the designated text with the source text.

[0137] Furthermore, in the above embodiment, the data analysis module 2034 of the server 20 performs various processes. However, the processes performed by the data analysis module 2034 may be executed by the artificial intelligence system 40. Specifically, the prompt generation module 2033 generates instructions related to the processes performed by the data analysis module 2034 as prompts, and the server 20 inputs the prompts into the large-scale language model of the artificial intelligence system 40, thereby receiving results similar to the results of the processes performed by the data analysis module 2034 from the large-scale language model. This allows the processes performed by the server 20 to be reduced.

[0138] The following is an example of the processing of the data analysis module 2034 that can be performed by the artificial intelligence system 40. A process of selecting a predetermined number of source sentences from multiple source sentences, and extracting information about the selected source sentences and information about the results of comparing the selected source sentences with a specified sentence from the response data. By outputting only information about the predetermined number of source sentences selected from multiple source sentences from a large-scale language model, the number of tokens can be reduced. - Sorting the response data for each source sentence based on a predetermined standard

[0139] In the above embodiment, the prompt does not specify an information source, as in the first example of the instruction 2028a, in which case the source sentence is extracted from an information source available to the artificial intelligence system 40. Alternatively, the information source from which the source sentence is extracted is specified, as in the second example of the instruction 2028a. However, the information source from which the artificial intelligence system 40 extracts the source sentence may be pre-trained. For example, the server 20 may input the information stored in the information source table 2022 into the large-scale language model of the artificial intelligence system 40 at a predetermined timing (e.g., at regular intervals), thereby learning information about the information sources stored in the information source table 2022. The prompt generation module 2033 may then generate a prompt including an instruction to extract the source sentence from the pre-trained information source.

[0140] In the above embodiment, the source sentence is extracted and compared with one designated sentence. However, multiple designated sentences may be specified by the user, and the source sentences may be extracted and compared with the multiple designated sentences.

[0141] In the above embodiment, the specified sentence is received by receiving text data input from the user to the operation object D11. However, the server 20 may receive web page identification information from the user instead of the text data of the specified sentence. The server 20 may then acquire the specified sentence from the web page based on the identification information. For example, the server 20 may acquire, as the specified sentence, a sentence published on a web page identified by the received identification information from an external server using any method. Examples of such methods include acquiring the web page text via an API published by the provider of the web page, acquiring the web page text using any web scraping technology, etc.

[0142] In the above embodiment, the designation of a sentence is accepted from the user, and the credibility of the designated sentence is determined. However, the designation of a poster of a sentence in a predetermined sentence posting service (SNS, etc.) may be accepted, and the credibility of multiple sentences posted by the designated poster (designated poster) may be determined.

[0143] For example, the user inputs identification information for identifying the poster on a reception screen displayed on the terminal device 10. The information for identifying the poster is information for identifying the poster's account in the text posting service (for example, the poster's user ID, the URL of the poster's personal page, etc.). The terminal device 10 transmits the received identification information to the server 20.

[0144] The server 20 acquires at least one sentence posted by the poster in the sentence posting service based on the received identification information. For example, the server 20 acquires one or more sentences posted by the poster in the sentence posting service via the API by transmitting the poster's ID to an API endpoint provided in the sentence posting service.

[0145] The server 20 acquires the credibility of the acquired sentence by executing the processes from step S13 onward of the sentence comparison process, with at least one acquired sentence as a designated sentence. At this time, for example, the prompt generation module 2033 includes an instruction such as "All #designated sentences are sentences posted by the same poster A. After outputting the credibility of #designated sentence, please decide the credibility of the poster by taking into consideration the credibility and #designated sentence, etc." in the prompt and inputs it into the large-scale language model, thereby obtaining the credibility of the poster from the large-scale language model.

[0146] The server 20 presents the acquired credibility of the poster to the user via the terminal device 10.

[0147] Furthermore, in the above embodiment, the reliability of an information source is determined, for example, by information in the "reliability" item in the information source table 2022, and this value is constant unless the value in the "perspective" item is changed. However, the reliability value may be increased or decreased as appropriate. Specifically, the value of the "perspective" item may be weighted based on the perspective that a provider or user of the service disclosed herein values, and the reliability value may be determined based on the weighted value of the "perspective" item.

[0148] In the above embodiment, the viewpoints are predefined in the instructions 2028b and 2028e. However, the viewpoints may be appropriately defined based on user input. For example, the reception screen D1 for the specified sentence may include an operation object for receiving an input operation of the viewpoint that the user values. The operation object may display, for example, the item name of the “viewpoint” item in the information source table 2022. When the user selects a viewpoint that the user values ​​from among the viewpoints displayed on the reception screen D1 for the specified sentence, the terminal device 10 transmits information related to the item of the received viewpoint to the server 20. The server 20 updates the instructions 2028b and 2028e in the prompt template 2028 with the item name of the received viewpoint, thereby generating a prompt based on the viewpoint that the user values.

[0149] In the above embodiment, in step S13, the server 20 generates a prompt including an instruction (first instruction) to extract at least one source sentence containing a description similar to the designated sentence from an information source available to the artificial intelligence system, and an instruction (second instruction) to compare the extracted source sentence with the designated sentence. The server 20 inputs the prompt including the first instruction and the second instruction into the large-scale language model and obtains a response. Based on the response from the large-scale language model, the server 20 presents to the user information about the extracted source sentence and a comparison result between the designated sentence and the source sentence.

[0150] However, the server 20 may generate a first prompt including a first instruction and input it to the large-scale language model. Then, based on the response data from the large-scale language model, information about the source sentence may be presented to the user. Then, the server 20 may receive from the user a specification of a source sentence to be compared with the specified sentence. Then, the server 20 may generate a second prompt including a second instruction to compare the specified sentence with the source sentence specified by the user and input it to the large-scale language model. Then, based on the response data from the large-scale language model, information about the comparison result between the source sentence specified by the user and the specified sentence may be presented to the user.

[0151] A specific example of the processing of this modified example will be described below: Fig. 12 is a flowchart showing an example of the processing of this modified example.

[0152] Steps S21 and S22 are similar to steps S11 and S12 of the sentence comparison process.

[0153] In step S23, the server 20 generates a prompt including the first instruction. Specifically, for example, the first prompt is generated by embedding the prompt information stored in the prompt information table 2023 in step S22 into a prompt template including the instruction 2028a.

[0154] In step S24, the server 20 inputs the generated first prompt into the large-scale language model provided by the artificial intelligence system 40. Specifically, for example, the server 20 sends a request including text data of the generated first prompt and necessary parameters (e.g., a specified number of tokens, etc.) to an API endpoint of the artificial intelligence system 40.

[0155] When the artificial intelligence system 40 receives a request from the server 20, it transmits response information including answer data from the large-scale language model to the server 20 via the API endpoint.

[0156] In step S25, the server 20 receives the response information sent from the artificial intelligence system 40.

[0157] In step S26, the server 20 extracts information about the source sentence from the answer data of the large-scale language model included in the response information. Specifically, for example, the server 20 extracts information about the following: The title of the source text (the title of the web page or article where the source text was published) The source from which the source text was extracted · Source reliability - The source of the source text (web page access destination, etc.) - Publication time of the source document (date, time, etc.) · The body of the source text

[0158] The server 20 generates an extraction result UI for presenting information about the source text to the user based on the information extracted from the response information. Specifically, for example, the server 20 generates the extraction result UI by inputting the extracted information for each item into a field provided in the extraction result UI corresponding to each item.

[0159] In step S27, the server 20 presents information about the extracted source sentences to the user. Specifically, the server 20 presents the generated extraction result UI to the user via the terminal device 10. For example, the server 20 causes the display 141 of the terminal device 10 to display an extraction result screen.

[0160] Fig. 13 is a schematic diagram showing an example of the extraction result screen D4. As shown in Fig. 12, the extraction result screen D4 includes an operation object D411, an operation object D412, an operation object D42, and a display object D43.

[0161] The operation objects D411 and D412 accept operations for inputting a request to narrow down the information about the source sentence displayed by the display object D43 based on a specific condition.

[0162] For example, when the operation object D411 accepts an input operation from the user, an object showing a list of items with predetermined reliability values ​​(90, 80, 70, etc.) or a list of items indicating the degree of reliability (high, medium, low, etc.) is displayed on the extraction result screen D4. For example, when the object accepts the specification of an item with a predetermined value, the information displayed by the display object D43 is narrowed down to information extracted from information sources having a reliability equal to or greater than the specified reliability value or degree. As an example, when an item with a reliability of "90" is specified, the information about the source sentence displayed by the display object D43 is narrowed down to information extracted from information sources with a reliability of "90" or greater.

[0163] Furthermore, for example, when the operation object D412 receives an input operation from the user, an object for specifying a date range is displayed on the extraction result screen D4. For example, when the object receives input of a predetermined date range, the information displayed by the display object D43 is narrowed down to information that was made public during the predetermined date range.

[0164] The operation object D42 accepts an operation to input a request to rearrange (sort) information about the source sentence displayed by the display object D43 based on a specific condition. For example, when the operation object D42 accepts an input operation from the user, a pull-down object for specifying a specific condition for the rearrangement, such as by reliability or date, is displayed on the extraction result screen D4. For example, when the object accepts the specification of a condition, the display object D43 is rearranged according to the specified condition. As an example, when the condition "by reliability" is specified, the display object D43 is rearranged in descending order of the reliability of the information source from which the extraction was made.

[0165] The display object D43 is an object that displays information about the source sentence. The display object D43 can also be said to be an object that displays information about each source sentence extracted as a candidate for comparison with the specified sentence. Specifically, for example, the display object D43 displays the following information about the extracted source sentence. The extraction result screen D4 has an independent display object D43 for each extracted source sentence. The title of the source text (the title of the web page or article where the source text was published) The source from which the source text was extracted · Source reliability - Publication time of the source document (date, time, etc.) · The body of the source text

[0166] Furthermore, each display object D43 includes an operation object D431 and an operation object D432. The operation object D431 and the operation object D432 receive an operation related to the source sentence related to the associated display object D43.

[0167] The operation object D431 accepts an operation for inputting a request to view a source sentence. For example, identification information (e.g., a URL link) of the extraction source of the source sentence is embedded in the operation object D431. When the operation object D431 accepts an input operation from the user, the terminal device 10 accesses the extraction source from the embedded link destination and presents information including the main text of the source sentence to the user.

[0168] The operation object D432 accepts an operation for inputting a request to compare a source sentence with a specified sentence. For example, when the operation object D432 accepts an input operation from a user, the terminal device 10 transmits information about the source sentence related to the operation object D432 to the server 20 together with a request to compare the source sentence with the specified sentence.

[0169] In addition, on the extraction result screen D4, the terminal device 10 may accept a request to compare a plurality of source sentences with the specified sentence. As an example, each operation object D432 related to each source sentence may be selectable in plurality at the same time.

[0170] In step S28, the server 20 accepts the request sent by the terminal device 10 by accepting the operation on the operation object D432 and information about the source sentence.

[0171] In step S29, server 20 generates a second prompt including a second instruction to compare the source sentence from which the information was received with the specified sentence. Specifically, for example, server 20 generates a prompt including an instruction to compare the specified sentence received in step S22 with the source sentence received in step S28.

[0172] (Example of the second prompt) While referring to #Information about source text, compare #Source text with #Specified text, and output the information according to the items in #Information about comparison results. #Information about the source text {Source text information} #Source text {source text} #specified text {specified text} #Information about comparison results - Matching parts of the specified sentence and the source sentence Differences between the specified text and the source text - Matching of the specified sentence with the source sentence · Basis for determining the degree of match

[0173] In the above example of the second prompt, information about the source sentence received in step S28 is inserted into {information about the source sentence}. The main text of the source sentence received in step S28 is inserted into {source sentence}. The specified sentence received in step S22 is inserted into {specified sentence}. The second prompt may also include sentences included in instructions 2028b to 2028e as appropriate. For example, the second prompt may include an instruction to output the credibility of the specified sentence received in step S22 based on the comparison result and the reliability of the information source of the source sentence received from terminal device 10.

[0174] In step S210, the server 20 inputs the generated second prompt into the large-scale language model provided by the artificial intelligence system 40.

[0175] When the artificial intelligence system 40 receives a request from the server 20, it transmits response information including answer data from the large-scale language model to the server 20 via the API endpoint.

[0176] In step S211, the server 20 receives the response information sent from the artificial intelligence system 40.

[0177] In step S212, the server 20 extracts information about the comparison result between the source sentence and the specified sentence from the answer data of the large-scale language model included in the response information.

[0178] The server 20 generates a comparison result UI for presenting information about the comparison result between the specified sentence and the source sentence to the user. Specifically, for example, the server 20 generates a comparison result UI according to the answer data by inputting information about the comparison result extracted from the answer data into fields provided in the comparison result UI corresponding to each item of the comparison result.

[0179] In step S213, the server 20 presents to the user information regarding the comparison result between the specified sentence received in step S22 and the source sentence about which information was received in step S28. Specifically, the server 20 presents the generated comparison result UI to the user via the terminal device 10. For example, the server 20 causes the display 141 of the terminal device 10 to display a comparison result screen.

[0180] Fig. 14 is a schematic diagram showing an example of the comparison result screen D5. As shown in Fig. 14, the comparison result screen D5 includes a display object D51, a display object D52, and a display object D53.

[0181] The display object D51 displays information about the source sentence about which the server 20 accepted the information in step S28. The display object D51 displays, for example, information similar to the information displayed by the display object D21 on the first results screen D2, about the source sentence about which the server 20 accepted the information in step S28.

[0182] The display object D52 displays information regarding the comparison result between the designated sentence received by the server 20 in step S22 and the source sentence about which information was received in step S28. Specifically, for example, the display object D52 displays information similar to the information displayed by the display object D22 on the first results screen D2 regarding the comparison result between the designated sentence received by the server 20 in step S22 and the source sentence about which information was received in step S28.

[0183] The display object D53 displays information related to the credibility of the designated sentence accepted by the server 20 in step S22. Specifically, for example, the display object D53 displays information related to the designated sentence accepted by the server 20 in step S22 that is similar to the information displayed by the display object D31 on the second results screen D3.

[0184] This completes the processing of this modified example. According to this modified example, in step S27, the server 20 presents the user with a list of source sentences extracted as candidates for comparison with the designated sentence. Then, in step S28, the server 20 accepts the designation of the source sentence to be compared with the designated sentence. Then, in step S213, the server 20 presents the designated source sentence and the comparison result between the designated sentence and the designated sentence to the user. This allows the user to select the source sentence to be compared with the designated sentence, so that the designated sentence and the source sentence can be compared according to the user's intention. This allows the user to more appropriately consider the credibility of the designated sentence.

[0185] <Summary> As described above, the server 20 accepts the specification of a sentence. The server 20 extracts at least one source sentence containing a description similar to the specified sentence from information sources available to the artificial intelligence system 40, and generates a prompt including an instruction to output information about the source sentence and an instruction to compare the extracted source sentence with the specified sentence. The server 20 inputs the prompt into a large-scale language model provided by the artificial intelligence system, and based on the answer obtained from the large-scale language model, presents information about the source sentence and a comparison result between the specified sentence and the source sentence to the user. This makes it possible to compare information disseminated in an unspecified field with information extracted from other information sources.

[0186] The prompt may also include instructions to extract the source sentence from at least one predetermined information source, thereby causing the artificial intelligence system 40 to extract the source sentence from a specific information source, such as an information source specified by the user.

[0187] Furthermore, a reliability level indicating the reliability of the information source is assigned to the information source. The prompt includes an instruction to output a reliability level indicating the reliability of the specified text based on the comparison result and the reliability level of the information source of the source text. The server 20 then presents the reliability level to the user, allowing the user to understand the reliability of the specified text.

[0188] The instructions also include instructions to determine the reliability of the information source of the source sentence based on at least one specific viewpoint. This allows the large-scale language model to determine the reliability of the information source. This reduces the burden on users, operators of the service disclosed herein, and the like to determine the reliability. Furthermore, the reliability can be determined objectively while eliminating subjectivity on users, operators of the service disclosed herein, and the like.

[0189] The prompt also includes an instruction to output a match score indicating the degree of match between the source sentence and the specified sentence. The server 20 then presents the match score to the user, allowing the user to more appropriately understand the comparison results between the source sentence and the specified sentence.

[0190] The prompt also includes instructions for outputting the basis for determining the degree of match. The server 20 presents the basis to the user, allowing the user to better understand the results of the comparison between the source sentence and the specified sentence.

[0191] The prompt also includes an instruction to output at least one of information regarding the matching portions and information regarding the differences between the specified sentence and the source sentence. The server 20 presents at least one of information regarding the matching portions and information regarding the differences between the specified sentence and the source sentence to the user. This allows the user to more appropriately understand the comparison results between the source sentence and the specified sentence.

[0192] Furthermore, when multiple source sentences are output from the large-scale language model, the server 20 presents a predetermined number of the multiple source sentences to the user based on a predetermined criterion, thereby simplifying the information about the source sentences displayed to the user and improving the visibility of the information about the source sentences.

[0193] Furthermore, when multiple source sentences are output from the large-scale language model, the presenting step presents information about the source sentences and the comparison results to the user in an order based on a predetermined criterion for the multiple source sentences, thereby organizing the information about the source sentences and the information about the comparison results displayed to the user and improving the visibility of the information about the source sentences and the information about the comparison results.

[0194] In addition, a reliability level indicating the degree of reliability of the information source is assigned to the information source. The predetermined criteria are standards regarding the reliability of the information source for each source sentence. This makes it possible to narrow down and sort information about the source sentence and comparison results according to the reliability of the information source.

[0195] The prompt also includes an instruction to output a degree of match between the source sentence and the specified sentence. The predetermined criteria are criteria for the degree of match between each source sentence and the specified sentence. This allows for filtering and sorting of information about the source sentences and the comparison results according to the degree of match.

[0196] Furthermore, each information source has a reliability level that indicates the reliability of the information source. When multiple source sentences are extracted, the prompt includes instructions to select at least one source sentence from the multiple source sentences based on the reliability of the information source from which the source sentence was extracted and compare it with the specified sentence. This allows the user to narrow down the source sentences to only those with a predetermined reliability level and compare them with the specified sentence. For example, the user can narrow down the source sentences extracted from highly reliable information sources and compare them with the specified sentence, making it easier to determine the credibility of the specified sentence. Furthermore, since the number of source sentences to be compared is narrowed down, the number of tokens consumed when using a large-scale language model can be reduced.

[0197] The specified text is a text contained in a post on a social networking service, which allows users to compare the post on the social networking service with information extracted from other sources.

[0198] <4 Basic computer hardware configuration> 15 is a block diagram showing the basic hardware configuration of a computer 90. The computer 90 includes at least a processor 94, a main memory device 95, an auxiliary memory device 96, and a communication IF (interface) 99. These are electrically connected to one another by a bus.

[0199] The processor 94 is hardware for executing an instruction set written in a program, and is composed of an arithmetic unit, registers, peripheral circuits, etc.

[0200] The main storage device 95 is used to temporarily store programs and data to be processed by the programs, etc. For example, it is a volatile memory such as a DRAM (Dynamic Random Access Memory).

[0201] The auxiliary storage device 96 is a storage device for saving data and programs, such as a flash memory, a hard disk drive (HDD), a magneto-optical disk, a CD-ROM, a DVD-ROM, or a semiconductor memory.

[0202] 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.

[0203] The network is composed of the Internet, LAN, various mobile communication systems constructed by wireless base stations, etc. For example, the network includes 3G, 4G, 5G mobile communication systems, LTE (Long Term Evolution), wireless networks that can connect to the Internet via a predetermined access point (e.g., Wi-Fi (registered trademark)), etc. In the case of a wireless connection, communication protocols include, for example, Z-Wave (registered trademark), ZigBee (registered trademark), Bluetooth (registered trademark), etc. In the case of a wired connection, the network also includes a network that is directly connected using a USB (Universal Serial Bus) cable, etc.

[0204] 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 90 housed in a single housing or case, but also a virtualized computer system.

[0205] <Basic functional configuration of computer 90> A description will be given of the functional configuration of a computer realized by the basic hardware configuration of a computer 90 shown in Fig. 14. The computer includes at least the functional units of a control unit, a storage unit, and a communication unit.

[0206] The functional units of the computer 90 can also be realized by distributing all or part of the functional units among multiple computers 90 interconnected via a network. The computer 90 is a concept that includes not only a single computer 90 but also a virtualized computer system.

[0207] The control unit is realized by the processor 94 reading various programs stored in the auxiliary storage device 96, expanding them in the main storage device 95, and executing processing in accordance with the programs. The control unit can realize functional units that perform various types of information processing depending on the type of program. In this way, the computer is realized as an information processing device that processes information.

[0208] The storage unit is realized by a main storage device 95 and an auxiliary storage device 96. The storage unit stores data, various programs, and various databases. Furthermore, the processor 94 can allocate a storage area corresponding to the storage unit in the main storage device 95 or the auxiliary storage device 96 in accordance with the programs. Furthermore, the control unit can cause the processor 94 to execute processes for adding, updating, and deleting data stored in the storage unit in accordance with the various programs.

[0209] A database refers to a relational database, which manages data sets called tables, which are structured by rows and columns, by relating them to 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.

[0210] Typically, each table 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 94 to add, delete, or update records in a specific table stored in the storage unit according to various programs.

[0211] The communication unit is realized by the communication IF 99. The communication unit realizes the function of communicating with other computers 90 via a network. The communication unit can receive information transmitted from other computers 90 and input the information to the control unit. The control unit can cause the processor 94 to execute information processing on the received information in accordance with various programs. Furthermore, the communication unit can transmit information output from the control unit to other computers 90.

[0212] The functions performed by the components described herein may be implemented in circuitry or processing circuitry, including general-purpose processors, application-specific processors, integrated circuits, ASICs (Application Specific Integrated Circuits), a CPU (a Central Processing Unit), conventional circuits, and / or combinations thereof, programmed to perform the described functions. A processor includes transistors and other circuits and is considered to be circuitry or processing circuitry. A processor may also be a programmed processor that executes programs stored in memory. In this specification, a circuitry, unit, or means is hardware that is programmed to realize or performs the described functions, which may be any hardware disclosed herein or any hardware known to be programmed to realize or perform the described functions. If the hardware is a processor considered to be a type of circuitry, the circuitry, means, or unit is a combination of the hardware and software used to configure the hardware and / or processor.

[0213] 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.

[0214] <Additional Notes> The matters described in the above embodiments will be supplemented below. (Appendix 1) A program for operating a computer, the program causing a processor of the computer to execute the following steps: accepting the specification of a sentence; extracting at least one source sentence containing a description similar to the specified sentence from an information source available to the artificial intelligence system, generating a prompt including instructions to output information about the source sentence and instructions to compare the extracted source sentence with the specified sentence; and presenting to a user information about the source sentence and the comparison result between the specified sentence and the source sentence based on an answer obtained from a large-scale language model provided by the artificial intelligence system by inputting the prompt into the large-scale language model. (Appendix 2) 2. The program of claim 1, wherein the prompt includes instructions to extract source sentences from at least one predetermined information source. (Appendix 3) The information source is assigned a credibility indicating the degree of reliability of the information source, and the prompt includes an instruction to output a credibility indicating the degree of reliability of the specified sentence based on the comparison result and the credibility of the information source of the source sentence, and in the presenting step, the credibility is presented to the user. (Appendix 4) 4. The program of claim 3, wherein the instructions include instructions for determining a credibility of an information source of the source sentence based on at least one particular viewpoint. (Appendix 5) A program described in any of Appendix 1 to Appendix 4, wherein the prompt includes instructions for outputting a degree of match indicating the degree of match between the source sentence and the specified sentence, and in the presenting step, the degree of match is presented to the user. (Appendix 6) 6. The program of claim 5, wherein the prompt includes an instruction to output a basis for determining the degree of match, and the presenting step presents the basis to the user. (Appendix 7) A program described in any of Appendix 1 to Appendix 6, wherein the prompt includes instructions for outputting at least one of information regarding the matching portions and information regarding the different portions between the specified sentence and the source sentence, and in the presenting step, at least one of information regarding the matching portions and information regarding the different portions between the specified sentence and the source sentence is presented to the user. (Appendix 8) 8. The program of claim 1, wherein, when multiple source sentences are output from a large-scale language model, in the presenting step, a predetermined number of source sentences from the multiple source sentences are presented to the user based on predetermined criteria. (Appendix 9) 9. The program of claim 1, wherein, when multiple source sentences are output from a large-scale language model, in the presenting step, information about the source sentences and comparison results are presented to the user in an order based on a predetermined criterion for the multiple source sentences. (Appendix 10) 10. The program of claim 8 or 9, wherein the information source has a reliability level indicating a degree of reliability of the information source, and the predetermined criteria are criteria regarding the reliability of the information source of each source sentence. (Appendix 11) 11. The program of any one of Appendixes 8 to 10, wherein the prompt includes instructions for outputting a degree of match between the source sentence and the specified sentence, and the predetermined criteria are criteria for the degree of match between each source sentence and the specified sentence. (Appendix 12) 12. The program of any one of Appendix 1 to Appendix 11, wherein the information source has a credibility level indicating a degree of trustworthiness of the information source, and the prompt includes instructions for, if multiple source sentences are extracted, selecting at least one source sentence from the multiple source sentences based on the credibility of the information source from which the source sentence was extracted and comparing it with the specified sentence. (Appendix 13) The program according to any one of Appendix 1 to Appendix 12, wherein the specified text is a text contained in a post on a social networking service. (Appendix 14) A method executed by a computer having a processor and a memory, the method comprising the steps of: receiving a specified sentence from an information source available to the artificial intelligence system; extracting at least one source sentence containing a description similar to the specified sentence, which is the specified sentence, from an information source available to the artificial intelligence system; generating a prompt including instructions to output information about the source sentence and instructions to compare the extracted source sentence with the specified sentence; and presenting to a user information about the source sentence and the comparison result between the specified sentence and the source sentence based on an answer obtained from the large-scale language model by inputting the prompt into a large-scale language model provided by the artificial intelligence system. (Appendix 15) An information processing device comprising a control unit and a memory unit, wherein the control unit executes the following steps: accepting the designation of a sentence; extracting at least one source sentence containing a description similar to the designated sentence from an information source available to the artificial intelligence system, generating a prompt including an instruction to output information about the source sentence and an instruction to compare the extracted source sentence with the designated sentence; and presenting to a user information about the source sentence and the comparison result between the designated sentence and the source sentence based on an answer obtained from the large-scale language model by inputting the prompt into a large-scale language model provided by the artificial intelligence system. (Appendix 16) A system including at least one information processing device having a control unit and a memory unit, which executes the steps of: accepting the designation of a sentence; extracting at least one source sentence containing a description similar to the designated sentence from an information source available to the artificial intelligence system, and generating a prompt including an instruction to output information about the source sentence and an instruction to compare the extracted source sentence with the designated sentence; and presenting to a user information about the source sentence and the comparison result between the designated sentence and the source sentence based on an answer obtained from the large-scale language model by inputting the prompt into a large-scale language model provided by the artificial intelligence system. [Explanation of symbols]

[0215] 1. System 10...Terminal device 12...Communication IF 120…Communications Department 13...Input device 131...Button 14...Output device 141...Display 15...Memory 150...Location information sensor 16…Storage 160...camera 17...Audio processing unit 171...Mike 172...Speaker 180...Storage section 19...Processor 190...Control unit 20...Server

Claims

1. A program for operating a computer, the program causing a processor of the computer to: accepting a specification of a sentence; generating a prompt including instructions for the artificial intelligence system to extract at least one source sentence containing a description similar to a designated sentence from available information sources, output information about the source sentence, and output information about the credibility of the designated sentence by comparing the extracted source sentence with the designated sentence; and a step of presenting to a user information about the source sentence, a comparison result between the specified sentence and the source sentence, and information about the credibility of the specified sentence based on an answer obtained from the large-scale language model provided by the artificial intelligence system by inputting the prompt into the large-scale language model.

2. The program of claim 1 , wherein the prompt includes instructions to extract the source sentence from at least one predetermined information source.

3. A reliability level indicating a degree of reliability of the information source is assigned to the information source; the prompt includes an instruction to output a credibility level indicating a degree of credibility of the specified sentence based on the comparison result and the credibility level of the information source of the source sentence; The program according to claim 1 , wherein the step of presenting the credibility includes presenting the credibility to the user.

4. The program of claim 3 , wherein the instructions include instructions for determining the trustworthiness of the information source of the source sentence based on at least one particular aspect.

5. the prompt includes instructions for outputting a match indicating the degree of match between the source sentence and the specified sentence; The program according to claim 1 , wherein the step of presenting the degree of match is to present the degree of match to the user.

6. the prompt includes an instruction to output a basis for determining the degree of match; The program according to claim 5 , wherein the presenting step presents the basis to the user.

7. the prompt includes an instruction to output at least one of information regarding a matching portion and information regarding a difference between the specified sentence and the source sentence; 2. The program according to claim 1, wherein the step of presenting at least one of information about the matching portion and information about the different portion between the specified sentence and the source sentence is presented to the user.

8. 2. The program according to claim 1, wherein, when a plurality of source sentences are output from the large-scale language model, in the presenting step, a predetermined number of the source sentences from the plurality of source sentences are presented to the user based on a predetermined criterion.

9. 2. The program of claim 1, wherein, when a plurality of source sentences are output from the large-scale language model, in the presenting step, information about the source sentences and the comparison results are presented to the user for the plurality of source sentences in an order based on a predetermined criterion.

10. A reliability indicating a degree of reliability of the information source is set for the information source, 10. The program according to claim 8, wherein the predetermined criterion is a criterion regarding the reliability of the information source of each source sentence.

11. the prompt includes an instruction for outputting a degree of agreement between the source sentence and the specified sentence; 10. The program according to claim 8, wherein the predetermined criterion is a criterion regarding the degree of match between each source sentence and the specified sentence.

12. A reliability indicating a degree of reliability of the information source is set for the information source, 2. The program of claim 1, wherein the prompt includes instructions for selecting at least one of the source sentences from the plurality of source sentences based on the reliability of the information source from which the source sentence was extracted and comparing the selected source sentence with the specified sentence, if multiple source sentences are extracted.

13. The program according to claim 1 , wherein the specified sentence is a sentence included in a post on a social networking service.

14. 1. A computer-implemented method comprising a processor and a memory, the method comprising: accepting a specification of a sentence; generating a prompt including instructions for the artificial intelligence system to extract at least one source sentence containing a description similar to a designated sentence from available information sources, output information about the source sentence, and output information about the credibility of the designated sentence by comparing the extracted source sentence with the designated sentence; A method for providing a user with information about the source sentence, a comparison result between the specified sentence and the source sentence, and information about the credibility of the specified sentence based on an answer obtained from the large-scale language model provided by the artificial intelligence system by inputting the prompt into the large-scale language model.

15. An information processing device including a control unit and a storage unit, wherein the control unit: accepting a specification of a sentence; generating a prompt including instructions for the artificial intelligence system to extract at least one source sentence containing a description similar to a designated sentence from available information sources, output information about the source sentence, and output information about the credibility of the designated sentence by comparing the extracted source sentence with the designated sentence; and presenting to a user information about the source sentence, a comparison result between the specified sentence and the source sentence, and information about the credibility of the specified sentence based on an answer obtained from the large-scale language model by inputting the prompt into the large-scale language model provided by the artificial intelligence system.

16. A system including at least one information processing device having a control unit and a storage unit, accepting a specification of a sentence; generating a prompt including instructions for the artificial intelligence system to extract at least one source sentence containing a description similar to a designated sentence from available information sources, output information about the source sentence, and output information about the credibility of the designated sentence by comparing the extracted source sentence with the designated sentence; A system that executes a step of presenting to a user information about the source sentence, a comparison result between the specified sentence and the source sentence, and information about the credibility of the specified sentence based on an answer obtained from the large-scale language model provided by the artificial intelligence system by inputting the prompt into the large-scale language model.

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