Contract text verification method, system and device based on knowledge warehouse and storage medium

Abstract

The application belongs to the technical field of information processing, and specifically discloses a contract text verification method, system and device based on a knowledge warehouse and a storage medium. The method comprises the following steps: performing text recognition on a to-be-verified contract text to obtain initial contract text content; performing multi-dimensional verification and risk content correction on the initial contract text content based on the knowledge warehouse; and finally, performing corresponding output and archiving on the contract text content after the risk content correction. The method can realize automatic recognition and evaluation of the contract text and complete efficient contract text verification. The multi-dimensional automatic verification of the contract text based on the knowledge warehouse can replace the traditional manual verification mode, greatly improve the auditing capacity and efficiency of the contract text, save labor costs, and realize automatic correction of risk clauses, thereby reducing omission or errors of the contract text.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of information processing, and particularly relates to a contract text verification method, system and device based on a knowledge warehouse and a storage medium. BACKGROUND

[0002] At present, the auditing of contracts by enterprises is mostly completed by contract auditors with professional knowledge and industry experience, which requires a high level of knowledge and industry experience of the contract auditors and a high difficulty and intensity of the contract auditing work, resulting in a low efficiency of manual auditing, a high labor cost and a high risk of missing details. Therefore, there is an urgent need for a more intelligent and efficient contract auditing and verification method. SUMMARY

[0003] The present application aims to provide a contract text verification method, system, device and storage medium based on a knowledge warehouse to solve the above problems in the prior art.

[0004] To achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0005] In a first aspect, a contract text verification method based on a knowledge warehouse is provided, comprising:

[0006] obtaining a contract text to be verified;

[0007] performing text recognition on the contract text to be verified to obtain initial contract text content;

[0008] performing multi-dimensional verification on the initial contract text content based on a pre-set knowledge warehouse to obtain a verification result, wherein the multi-dimensional verification includes semantic analysis, context analysis, context logic analysis and integrity analysis, and the knowledge warehouse is trained by a natural language processing algorithm based on a plurality of contract content samples;

[0009] when it is determined according to the verification result that the initial contract text content contains risk content that can be corrected by the knowledge warehouse, correcting the risk content based on the knowledge warehouse to obtain contract text content after correction of the risk content;

[0010] sending the contract text content after correction of the risk content to an artificial auditing end and receiving an artificial auditing result fed back by the artificial auditing end;

[0011] when it is determined according to the artificial auditing result that the artificial auditing is passed, outputting the contract text content after correction of the risk content and archiving the contract text content after correction of the risk content.

[0012] In one possible design, when it is determined according to the verification result that the initial contract text content contains risk content that cannot be corrected by the knowledge warehouse, the method further comprises:

[0013] marking risk content that cannot be corrected by the knowledge warehouse in the initial contract text content;

[0014] sending the marked initial contract text content to the artificial review end and receiving the artificial correction contract text content fed back by the artificial review end;

[0015] determining artificial correction risk content based on the artificial correction contract text content;

[0016] outputting the artificial correction contract text content, archiving the artificial correction contract text content, and updating the artificial correction risk content to the knowledge warehouse.

[0017] In one possible design, the multi-dimensional verification of the initial contract text content based on the preset knowledge warehouse includes:

[0018] determining the contract attribute of the initial contract text content;

[0019] extracting the corresponding attribute value of each contract clause in the initial contract text content and the context corresponding to the attribute value according to the contract attribute;

[0020] performing semantic analysis and context analysis on the attribute value of each contract clause and the context corresponding to the attribute value based on the knowledge warehouse to obtain context semantic analysis results, and summarizing the context semantic analysis results into the verification results.

[0021] In one possible design, the multi-dimensional verification of the initial contract text content based on the preset knowledge warehouse includes:

[0022] determining the contract attribute of the initial contract text content;

[0023] importing the contract attribute into the knowledge warehouse, and determining a plurality of integrity audit keywords corresponding to the contract attribute in the knowledge warehouse;

[0024] performing integrity analysis on the initial contract text content by using the plurality of integrity audit keywords to obtain integrity analysis results, and summarizing the integrity analysis results into the verification results.

[0025] In one possible design, the multi-dimensional verification of the initial contract text content based on the preset knowledge warehouse includes:

[0026] determining the contract attribute of the initial contract text content;

[0027] importing the contract attribute into the knowledge warehouse, and determining a context logic audit rule corresponding to the contract attribute in the knowledge warehouse;

[0028] Context logic auditing rules are used to audit the initial contract text content based on the context logic, and context logic analysis results are obtained, which are summarized into the verification results.

[0029] In one possible design, when the risk content is modified based on the knowledge warehouse, the method further includes: labeling the modified risk content with a set identifier, so that the contract text content after the risk content is modified contains the labeled modified risk content.

[0030] When the contract text content after the risk content is modified is output, the method further includes: deleting the set identifier marked in the contract text content after the risk content is modified, and then outputting.

[0031] In one possible design, the contract text content after the risk content is modified is archived, including:

[0032] The contract text content after the risk content is modified is versioned and stored in a corresponding database for archiving;

[0033] The contract text content after the risk content is modified is chained and stored in a blockchain.

[0034] In a second aspect, a contract text verification system based on a knowledge warehouse is provided, including an acquisition unit, an identification unit, a verification unit, a modification unit, a marking unit, a transceiving unit, a determination unit, an archiving unit and an updating unit, wherein:

[0035] The acquisition unit is configured to acquire a contract text to be verified.

[0036] The identification unit is configured to perform text identification on the contract text to be verified to obtain initial contract text content.

[0037] The verification unit is configured to perform multi-dimensional verification on the initial contract text content based on a preset knowledge warehouse to obtain verification results, wherein the multi-dimensional verification includes semantic analysis, context analysis, context logic analysis and integrity analysis, and the knowledge warehouse is obtained by training a plurality of contract content samples using a natural language processing algorithm.

[0038] The modification unit is configured to modify the risk content based on the knowledge warehouse when it is determined according to the verification results that the initial contract text content contains risk content that can be modified by the knowledge warehouse, to obtain contract text content after the risk content is modified.

[0039] The marking unit is configured to mark the risk content that cannot be modified by the knowledge warehouse in the initial contract text content when it is determined according to the verification results that the initial contract text content contains risk content that cannot be modified by the knowledge warehouse.

[0040] The transceiving unit is configured to send the contract text content with the risk content revised to the artificial auditing end, receive the artificial auditing result fed back by the artificial auditing end, and send the initial contract text content with the mark completed to the artificial auditing end and receive the artificial revised contract text content fed back by the artificial auditing end;

[0041] The determining unit is configured to determine the artificial revised risk content based on the artificial revised contract text content.

[0042] The archiving unit is configured to output the contract text content with the risk content revised and archive the contract text content with the risk content revised when it is determined that the artificial auditing is passed according to the artificial auditing result, and output the artificial revised contract text content and archive the artificial revised contract text content.

[0043] The updating unit is configured to update the artificial revised risk content to the knowledge warehouse.

[0044] In a third aspect, a contract text verification device based on a knowledge warehouse is provided, comprising:

[0045] A memory is configured to store instructions.

[0046] A processor is configured to read the instructions stored in the memory and execute the method according to any one of the first aspect according to the instructions.

[0047] In a fourth aspect, a computer readable storage medium is provided, and the computer readable storage medium stores instructions, when the instructions are run on a computer, the computer is caused to execute the method according to any one of the first aspect. Meanwhile, a computer program product containing instructions is also provided, when the instructions are run on a computer, the computer is caused to execute the method according to any one of the first aspect.

[0048] Beneficial effects: the contract text to be verified is subjected to text recognition to obtain initial contract text content, then the initial contract text content is subjected to multi-dimensional verification and risk content revision based on the knowledge warehouse, and finally the contract text content with the risk content revised is output and archived correspondingly, so that automatic recognition and evaluation of the contract text can be realized, and efficient contract text verification can be completed. The multi-dimensional automatic verification of the contract text based on the knowledge warehouse can replace the traditional artificial verification mode, greatly improve the auditing capability and efficiency of the contract text, save labor cost, and realize automatic revision of the risk clauses, and reduce omission or errors of the clauses of the contract text. BRIEF DESCRIPTION OF DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced. Obviously, the accompanying drawings in the following description only only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of these drawings.

[0050] Figure 1 The schematic diagram of the steps of the method in Embodiment 1 of the present application is shown.

[0051] Figure 2 The schematic diagram of the constitution of the system in Embodiment 2 of the present application is shown.

[0052] Figure 3 The schematic diagram of the constitution of the device in Embodiment 3 of the present application is shown. DETAILED DESCRIPTION

[0053] It should be noted that the description of these embodiments is used to help understand the present application, but does not constitute a limitation of the present application. The specific structure and functional details disclosed herein are only used to describe the example embodiments of the present application. However, the present application can be embodied in many alternative forms, and should not be understood as limited in the embodiments set forth herein.

[0054] It should be understood that unless otherwise explicitly specified and limited, the term "connection" should be understood broadly, for example, it can be a fixed connection, or a detachable connection, or an integral connection; it can be a mechanical connection, or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, or it can be the internal communication of two elements. For those skilled in the art, the specific meaning of the above-mentioned term in the embodiments can be understood according to the specific circumstances.

[0055] In the following description, specific details are provided to facilitate a full understanding of the example embodiments. However, those skilled in the art should understand that the example embodiments can be implemented without these specific details. For example, systems can be shown in block diagrams to avoid unnecessary details that make the examples unclear. In other embodiments, well-known processes, structures and techniques can not be shown in unnecessary details to avoid obscuring the embodiments.

[0056] Embodiment 1:

[0057] The present embodiment provides a contract text verification method based on a knowledge warehouse, which can be applied to a corresponding contract auditing platform, such as Figure 1 As shown, the method comprises the following steps:

[0058] S1. Obtain the contract text to be verified.

[0059] In specific implementation, the platform needs to obtain the contract text to be verified, which can be obtained through local text uploading or online text transmission.

[0060] S2. Text recognition is performed on the contract text to be verified to obtain initial contract text content.

[0061] In specific implementation, the platform can use optical character recognition technology to perform text scanning and recognition on the contract text to be verified to extract the initial contract text content.

[0062] S3. Multi-dimensional verification is performed on the initial contract text content based on a preset knowledge warehouse to obtain a verification result, the multi-dimensional verification including semantic analysis, context analysis, context logic analysis and integrity analysis, and the knowledge warehouse being trained by a natural language processing algorithm based on a plurality of contract content samples.

[0063] In specific implementation, after the initial contract text content is recognized, the platform can perform multi-dimensional verification including semantic analysis, context analysis, context logic analysis and integrity analysis on the initial contract text content based on a preset knowledge warehouse to obtain a corresponding verification result. The knowledge warehouse is trained by a natural language processing algorithm based on a plurality of contract content samples to enhance the semantic understanding ability of the artificial intelligence algorithm for contracts, so that the key elements of a contract can be accurately extracted to form a corresponding data model, and the contract verification efficiency is doubled.

[0064] The data model of the knowledge warehouse can quickly find the most suitable template from a large number of contract templates, help users avoid potential legal risks, and improve the efficiency and quality of contract verification. The knowledge warehouse focuses on semantic comparison through natural language processing technology to exclude interference caused by text format, punctuation, space and other factors, so that the comparison result is more accurate. Meanwhile, the natural language processing technology and knowledge graph and other artificial intelligence technologies can be combined to improve the contract auditing capability, realize classification identification and risk assessment of the contract, so as to replace the manual auditing mode to complete the intelligent examination of the contract and give corresponding modification information.

[0065] Exemplarily, the knowledge warehouse is based on a huge and complex data warehouse, which can cover various legal content. Through machine learning, various legal systems are modeled, trained and learned to adapt to the inspection and application of various contract attributes. For example, when checking the generated contract text content, the intelligent review encounters "the contract is valid for 3 years, and the confidentiality agreement is generated during the entire contract validity period". Because the platform knowledge warehouse has learned contract law and stored the training results in the data warehouse, and the case in this example applies to a certain clause in the contract law, at this time, the knowledge warehouse can review and correct the contract text content based on the knowledge warehouse, archive the contract text content after this time of labeling and correction, label and retain it, provide a basis for subsequent auditing and tracing, and continue to empower subsequent contract template generation and contract file auditing.

[0066] When the platform checks the initial contract text content based on the knowledge warehouse, it can first determine the contract attributes of the initial contract text content, extract the corresponding attribute values of each contract clause in the initial contract text content, such as the term, amount, quantity, etc., and the context corresponding to the attribute values, based on the knowledge warehouse. The semantic analysis and context analysis of the attribute values of each contract clause and the context corresponding to the attribute values are performed to obtain the context semantic analysis result, which is summarized in the verification result. At the same time, semantic and context analysis can also be completed in the knowledge warehouse to complete user profiling and classify users. Exemplarily, such as reviewing the full text and contacting the context to know whether the user is an upstream industrial manufacturer or a downstream clinic or hospital, such as the content containing "each piece of traditional Chinese medicine contains 0.02g licorice, 0.03g cassia bark, 1.32g deer horn, etc., and the production process is drying in a dry and constant temperature environment, and the packaging is completed by 12 square centimeters of aluminum foil", after the analysis, it is determined that the user is an upstream pharmaceutical enterprise, then the background investigation of the pharmaceutical enterprise is carried out, and the corresponding legal risk prompt of the enterprise is carried out.

[0067] When the platform checks the initial contract text content based on the knowledge warehouse, it can first determine the contract attributes of the initial contract text content, import the contract attributes into the knowledge warehouse, determine the several integrity audit keywords corresponding to the contract attributes in the knowledge warehouse, and then use the several integrity audit keywords to analyze the integrity of the initial contract text content. Determine whether the contract text content contains the corresponding integrity audit keywords to obtain the integrity analysis result, and summarize the integrity analysis result in the verification result.

[0068] The platform can first determine the contract attribute of the initial contract text content, import the contract attribute into the knowledge warehouse, determine the context logic audit rule corresponding to the contract attribute in the knowledge warehouse, which can include a plurality of preset logical audit attributes and the logical relationship between the plurality of logical audit attributes in the contract text clause, then perform context logic audit on the initial contract text content based on the context logic audit rule, and obtain a context logic analysis result, and then summarize the context logic analysis result into a verification result.

[0069] S4. When it is determined according to the verification result that the initial contract text content contains risk content that can be modified by the knowledge warehouse, the risk content is modified based on the knowledge warehouse to obtain contract text content after modification of the risk content.

[0070] In specific implementation, after the platform performs multi-dimensional verification on the initial contract text content based on the knowledge warehouse, a corresponding verification result is obtained. When it is determined according to the verification result that the initial contract text content contains risk content that can be modified by the knowledge warehouse, the risk content is modified based on the knowledge warehouse, and the modified risk content is marked with a set identifier, such as bold font and color marking, to obtain contract text content after modification of the risk content. The contract text content after modification of the risk content contains the marked modified risk content.

[0071] S5. The contract text content after modification of the risk content is sent to the artificial audit end, and an artificial audit result fed back by the artificial audit end is received.

[0072] In specific implementation, the platform sends the contract text content after modification of the risk content to the artificial audit end, and the artificial audit end performs semi-automatic artificial audit and confirmation on the marked modified risk content, thereby improving the efficiency of personnel audit. Subsequently, the platform receives the artificial audit result fed back by the artificial audit end. When it is determined according to the verification result that the initial contract text content contains risk content that cannot be modified by the knowledge warehouse, the platform can mark the risk content that cannot be modified by the knowledge warehouse in the initial contract text content based on the knowledge warehouse, and send the marked initial contract text content to the artificial audit end. The artificial audit end audits and modifies the marked risk content that cannot be modified. Subsequently, the platform receives the artificial modified contract text content fed back by the artificial audit end.

[0073] S6. When it is determined according to the artificial audit result that the artificial audit is passed, the contract text content after modification of the risk content is output, and the contract text content after modification of the risk content is archived.

[0074] In specific implementation, when the platform determines that the manual review is passed according to the manual review result, the platform outputs the contract text content with the risk content corrected, including removing the set mark marked in the contract text content with the risk content corrected, and then outputting, and archiving the contract text content with the risk content corrected. Alternatively, after receiving the contract text content after manual correction, the platform outputs the contract text content after manual correction, and archives the contract text content after manual correction, and simultaneously determines the risk content after manual correction based on the contract text content after manual correction; outputs the contract text content after manual correction, and archives the contract text content after manual correction, updates the risk content after manual correction to the knowledge warehouse, and realizes optimization and upgrading of the knowledge warehouse, so as to be used for automatic contract text verification and correction in the next round. When archiving the contract text content with the risk content corrected, or archiving the contract text content after manual correction, the platform performs version trace on the corrected contract text content, and stores the corrected contract text content in the corresponding database for archiving, and then uploads the corrected contract text content to the blockchain through time stamp and blockchain technology, and stores the corrected contract text content in the blockchain, so as to ensure that the contract content is not tampered with.

[0075] The method of the embodiment can replace the traditional manual verification mode, greatly improve the contract text auditing capability and efficiency, save labor cost, and realize automatic correction of risk clauses and reduce omission or errors of contract text clauses.

[0076] Embodiment 2

[0077] The embodiment provides a contract text verification system based on a knowledge warehouse, as shown in Figure 2 The contract text verification system based on the knowledge warehouse includes an acquisition unit, an identification unit, a verification unit, a correction unit, a marking unit, a transceiving unit, a determination unit, an archiving unit, and an updating unit, wherein:

[0078] The acquisition unit is configured to acquire a contract text to be verified.

[0079] The identification unit is configured to perform text identification on the contract text to be verified to obtain initial contract text content.

[0080] The verification unit is configured to perform multi-dimensional verification on the initial contract text content based on a preset knowledge warehouse to obtain a verification result, wherein the multi-dimensional verification includes semantic analysis, context analysis, context logic analysis, and integrity analysis, and the knowledge warehouse is obtained by training a plurality of contract content samples using a natural language processing algorithm.

[0081] The correction unit is configured to correct the risk content based on the knowledge warehouse to obtain contract text content with the risk content corrected when it is determined according to the verification result that the initial contract text content contains risk content that can be corrected by the knowledge warehouse.

[0082] The marking unit is used to mark the risk content that the knowledge warehouse cannot correct in the initial contract text content when it is determined from the verification result that the initial contract text content contains risk content that the knowledge warehouse cannot correct.

[0083] The sending and receiving unit is used to send the contract text content after the risk content is corrected to the manual review end, and receive the manual review results from the manual review end, as well as send the initial contract text content marked as completed to the manual review end, and receive the manually corrected contract text content from the manual review end.

[0084] The determination unit is used to identify the content of manually revised risks based on the content of the manually revised contract text.

[0085] The archiving unit is used to output and archive the revised contract text after the manual review is deemed successful, and also to output and archive the manually revised contract text.

[0086] The update unit is used to update manually corrected risky content to the knowledge repository.

[0087] Example 3:

[0088] This embodiment provides a contract text verification device based on a knowledge repository, such as... Figure 3 As shown, at the hardware level, it includes:

[0089] The data interface is used to establish data communication between the processor and external terminals;

[0090] Memory, used to store instructions;

[0091] The processor is used to read instructions stored in the memory and execute the contract text verification method in Embodiment 1 according to the instructions.

[0092] Optionally, the device also includes an internal bus. The processor, memory, and data interface can be interconnected via the internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc.

[0093] The memory can include, but is not limited to, a random access memory (RAM), a read only memory (ROM), a flash memory, a first in first out memory (FIFO), a first in last out memory (FILO), and / or the like. The processor can be a general purpose processor, including a central processing unit (CPU), a network processor (NP), and / or the like; and can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic component, a discrete hardware component, and / or the like.

[0094] Embodiment 4

[0095] The embodiment provides a computer readable storage medium, and instructions are stored on the computer readable storage medium. When the instructions are run on a computer, the computer executes the contract text verification method in the embodiment 1. The computer readable storage medium is a carrier for storing data, and can include, but is not limited to, a floppy disk, a compact disc, a hard disk, a flash memory, a USB flash disk, a memory stick, and / or the like. The computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable system.

[0096] The embodiment also provides a computer program product containing instructions, and the instructions are run on a computer to make the computer execute the contract text verification method in the embodiment 1. The computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable system.

[0097] Finally, it should be noted that: the above only describes the preferred embodiments of the present application and is not used to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, and / or the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A contract text verification method based on a knowledge repository, characterized in that, include: Obtain the contract text to be verified; The contract text to be verified is subjected to text recognition to obtain the initial contract text content; The initial contract text content is validated in multiple dimensions based on a pre-built knowledge repository to obtain validation results. The multi-dimensional validation includes semantic analysis, contextual analysis, contextual logic analysis, and integrity analysis. The knowledge repository is trained using a natural language processing algorithm with several contract content samples. When the initial contract text content is determined to contain risk content that can be corrected by the knowledge repository based on the verification results, the risk content is corrected based on the knowledge repository to obtain the contract text content with corrected risk content. Send the revised contract text with the risk content to the manual review platform and receive the manual review results from the platform. When the manual review is deemed successful, the revised contract text with corrected risk content is output and archived. Specifically, when the initial contract text content is determined to contain risk content that can be corrected by the knowledge repository based on the verification results, the risk content is corrected based on the knowledge repository to obtain the contract text content after risk content correction. This includes: performing multi-dimensional verification on the initial contract text content based on the knowledge repository to obtain the verification results; when the initial contract text content is determined to contain risk content that can be corrected by the knowledge repository based on the verification results, the risk content is corrected based on the knowledge repository; and the corrected risk content is marked with a flag to obtain the contract text content after risk content correction. The process involves sending the revised contract text with corrected risk content to a human reviewer and receiving the human review results. Specifically, this includes: sending the revised contract text with corrected risk content to a human reviewer for manual review and confirmation of the corrected risk content, and then receiving the human review results from the human reviewer; if the initial contract text contains risk content that cannot be corrected by the knowledge repository based on the verification results, the human reviewer marks the risk content that cannot be corrected by the knowledge repository in the initial contract text, and then sends the marked initial contract text to the human reviewer for manual review and modification of the marked uncorrectable risk content. Specifically, when the manual review is deemed successful, the platform outputs and archives the revised contract text with corrected risk content. This includes: when the platform determines that the manual review has passed, it outputs the revised contract text with corrected risk content, including removing the specified markers from the revised contract text before outputting it, and then archiving the revised contract text; or, after receiving the manually revised contract text, it outputs the manually revised contract text and archives it, while simultaneously determining the manually corrected risk content based on the manually revised contract text; the manually corrected risk content is updated to the knowledge repository to optimize and upgrade the knowledge repository for the next round of automatic contract text verification and correction; when archiving the revised contract text with corrected risk content, or archiving the manually corrected contract text, version tracking is performed on the revised contract text, and it is stored in the corresponding database for archiving. Then, the revised contract text is timestamped and stored on the blockchain using blockchain technology.

2. The contract text verification method based on a knowledge repository according to claim 1, characterized in that, When determining, based on the verification results, that the initial contract text contains risky content that the knowledge repository cannot correct, the method further includes: Mark risky content that the knowledge repository cannot correct in the initial contract text; Send the marked initial contract text to the human reviewer and receive the manually revised contract text from the human reviewer. The risks associated with manual corrections are determined based on the content of the manually revised contract text. Output the manually revised contract text and archive the manually revised contract text. Update the manually revised risk content to the knowledge repository.

3. The contract text verification method based on a knowledge repository according to claim 1, characterized in that, The multi-dimensional verification of the initial contract text content based on the pre-built knowledge repository includes: Determine the contract attributes of the initial contract text content; Extract the corresponding attribute values ​​and the context of each contract clause from the initial contract text based on the contract attributes; Based on the knowledge repository, semantic and contextual analysis is performed on the attribute values ​​of each contract clause and the context corresponding to the attribute values ​​to obtain contextual semantic analysis results, which are then summarized into the verification results.

4. The contract text verification method based on a knowledge repository according to claim 1, characterized in that, The multi-dimensional verification of the initial contract text content based on the pre-built knowledge repository includes: Determine the contract attributes of the initial contract text content; Import the contract attributes into the knowledge repository and identify several integrity audit keywords corresponding to the contract attributes in the knowledge repository; The integrity analysis of the initial contract text is performed using the aforementioned integrity audit keywords, and the integrity analysis results are then summarized into the verification results.

5. The contract text verification method based on a knowledge repository according to claim 1, characterized in that, The multi-dimensional verification of the initial contract text content based on the pre-built knowledge repository includes: Determine the contract attributes of the initial contract text content; Import the contract attributes into the knowledge repository and determine the context logic audit rules corresponding to the contract attributes in the knowledge repository; The initial contract text content is reviewed based on the aforementioned context logic review rules to obtain context logic analysis results, which are then summarized into the verification results.

6. A contract text verification system based on a knowledge repository, characterized in that, It includes an acquisition unit, an identification unit, a verification unit, a correction unit, a marking unit, a transmission and reception unit, a determination unit, an archiving unit, and an update unit, wherein: The acquisition unit is used to acquire the contract text to be verified. The recognition unit is used to perform text recognition on the contract text to be verified to obtain the initial contract text content. The verification unit is used to perform multi-dimensional verification on the initial contract text content based on a pre-set knowledge repository to obtain the verification result. The multi-dimensional verification includes semantic analysis, contextual analysis, contextual logic analysis and integrity analysis. The knowledge repository is obtained by training a number of contract content samples using a natural language processing algorithm. The correction unit is used to correct the risk content based on the knowledge repository when the initial contract text content is determined to contain risk content that can be corrected according to the verification result, so as to obtain the contract text content with corrected risk content. The marking unit is used to mark the risk content that the knowledge warehouse cannot correct in the initial contract text content when it is determined from the verification result that the initial contract text content contains risk content that the knowledge warehouse cannot correct. The sending and receiving unit is used to send the contract text content after the risk content is corrected to the manual review end, and receive the manual review results from the manual review end, as well as send the initial contract text content marked as completed to the manual review end, and receive the manually corrected contract text content from the manual review end. The determination unit is used to identify the content of manually revised risks based on the content of the manually revised contract text. The archiving unit is used to output and archive the revised contract text after the manual review is deemed successful, and also to output and archive the manually revised contract text. The update unit is used to update manually corrected risky content to the knowledge repository; Specifically, when the initial contract text content is determined to contain risk content that can be corrected by the knowledge repository based on the verification results, the risk content is corrected based on the knowledge repository to obtain the contract text content after risk content correction. This includes: performing multi-dimensional verification on the initial contract text content based on the knowledge repository to obtain the verification results; when the initial contract text content is determined to contain risk content that can be corrected by the knowledge repository based on the verification results, the risk content is corrected based on the knowledge repository; and the corrected risk content is marked with a flag to obtain the contract text content after risk content correction. The process involves sending the revised contract text with corrected risk content to a human reviewer and receiving the human review results. Specifically, this includes: sending the revised contract text with corrected risk content to a human reviewer for manual review and confirmation of the corrected risk content, and then receiving the human review results from the human reviewer; if the initial contract text contains risk content that cannot be corrected by the knowledge repository based on the verification results, the human reviewer marks the risk content that cannot be corrected by the knowledge repository in the initial contract text, and then sends the marked initial contract text to the human reviewer for manual review and modification of the marked uncorrectable risk content. Specifically, when the manual review is deemed successful, the platform outputs and archives the revised contract text with corrected risk content. This includes: when the platform determines that the manual review has passed, it outputs the revised contract text with corrected risk content, including removing the specified markers from the revised contract text before outputting it, and then archiving the revised contract text; or, after receiving the manually revised contract text, it outputs the manually revised contract text and archives it, while simultaneously determining the manually corrected risk content based on the manually revised contract text; the manually corrected risk content is updated to the knowledge repository to optimize and upgrade the knowledge repository for the next round of automatic contract text verification and correction; when archiving the revised contract text with corrected risk content, or archiving the manually corrected contract text, version tracking is performed on the revised contract text, and it is stored in the corresponding database for archiving. Then, the revised contract text is timestamped and stored on the blockchain using blockchain technology.

7. A contract text verification device based on a knowledge repository, characterized in that, include: Memory, used to store instructions; A processor is configured to read instructions stored in the memory and execute the contract text verification method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the contract text verification method according to any one of claims 1-5.

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