Contract text labeling method, device and equipment

Abstract

The invention provides a contract text labeling method, device and equipment. The method comprises the following steps: acquiring a contract text to be labeled; inputting a to-be-labeled contract text into the labeling model, and outputting a labeling result of the contract text; the labeling model is used for identifying information related to the evaluation standard in the contract text and labeling the contract text. According to the method provided by the embodiment of the invention, the efficiency and accuracy of contract text labeling are improved, and the problems of low efficiency and high error rate in manual contract labeling in related technologies are effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of contract text analysis, and in particular to a contract text annotation method, device and equipment. Background Art

[0002] As contract management becomes increasingly complex and sophisticated, the demand for querying and retrieving contract data elements is growing. Currently, contract annotation relies primarily on manual labor, which is inefficient and prone to errors. Therefore, how to accurately and efficiently annotate contract texts is a technical challenge that those skilled in the art urgently need to address. Summary of the Invention

[0003] The present invention provides a method, device and equipment for annotating contract texts. By inputting the contract text to be annotated into an annotation model, the annotation model can be used to quickly and accurately identify the evaluation standard related information in the contract text, thereby efficiently and accurately annotating the contract text, improving the efficiency and accuracy of contract text annotation, and effectively solving the low efficiency and error-prone problems of manual contract annotation in related technologies.

[0004] The present invention provides a method for marking a contract text, comprising the following steps.

[0005] Get the contract text to be annotated; The contract text to be annotated is input into an annotation model, and an annotation result of the contract text is output; the annotation model is used to identify the evaluation standard related information in the contract text and annotate the contract text.

[0006] According to a contract text annotation method provided by the present invention, the annotation model includes: The first annotation sub-model; wherein, The first annotation sub-model is used to obtain image information corresponding to the contract text, identify information related to the evaluation criteria from the image information, and perform annotation.

[0007] According to a contract text annotation method provided by the present invention, the annotation model further includes: The second annotation sub-model; wherein, The second annotation sub-model is used to match and annotate information related to the evaluation criteria from the contract text based on a preset regular expression.

[0008] According to a contract text annotation method provided by the present invention, the second annotation sub-model is further used to: Semantic transformation is performed based on fuzzy logic to identify and annotate the evaluation criteria-related information in the contract text.

[0009] According to a contract text annotation method provided by the present invention, the second annotation sub-model is further used to: Based on syntactic analysis, target sentence patterns in the contract text that are relevant to the evaluation criteria are identified; and the contract text is annotated based on the content of the target sentence patterns.

[0010] According to a method for marking a contract text provided by the present invention, the method further includes: Construct a target operation interface; the target operation interface supports uploading contract documents, viewing annotation results, and adjusting annotation parameters.

[0011] The present invention also provides a contract text annotation device, comprising the following modules: The acquisition module is used to obtain the contract text to be annotated; The annotation module is used to input the contract text to be annotated into the annotation model and output the annotation result of the contract text; the annotation model is used to identify the evaluation standard related information in the contract text and annotate the contract text.

[0012] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for marking a contract text as described above is implemented.

[0013] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described contract text annotation methods.

[0014] The present invention also provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above-described contract text annotation methods.

[0015] The contract text annotation method, device and equipment provided by the present invention input the contract text to be annotated into the annotation model, and can quickly and accurately identify the evaluation standard related information in the contract text through the annotation model, so as to efficiently and accurately realize the annotation of the contract text, improve the efficiency and accuracy of the contract text annotation, and effectively solve the low efficiency and error-prone problems existing in the related technology when relying on manual contract annotation. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 This is one of the flow charts of the contract text annotation method provided by the present invention.

[0018] Figure 2 This is the second flow chart of the contract text annotation method provided by the present invention.

[0019] Figure 3 It is a structural schematic diagram of the contract text annotation device provided by the present invention.

[0020] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0021] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0022] The following combination Figures 1-4 The present invention describes the contract text annotation method, device and equipment.

[0023] In order to facilitate a clearer understanding of the technical solutions of the various embodiments of the present application, some technical contents related to the various embodiments of the present application are first introduced.

[0024] As contract management becomes increasingly complex and sophisticated, the demand for querying and retrieving contract data elements is growing. Existing technologies often rely on manual operations for contract annotation, which is inefficient, costly, and prone to missing key clauses. Traditional automated methods struggle to cope with the complexity of contract texts (e.g., nested clauses, cross-references to multiple standards, etc.). Existing technologies are particularly lacking in deep semantic parsing and multi-dimensional correlation capabilities for contract evaluations, given their unique evaluation standards (e.g., ISO standards, CMMM, ITSS), assessment levels (e.g., maturity level 3), and dynamically updated compliance requirements.

[0025] For example, the main defects in the related art are as follows: (1) Contract text annotation is a tedious task, and manual annotation is inefficient and prone to omissions or errors.

[0026] (2) The evaluation standards and levels involved in the contract text are diverse, and manual annotation is difficult to ensure consistency.

[0027] (3) There is a lack of a unified annotation method and system, which cannot meet the needs of automated processing of large-scale contract texts.

[0028] (4) The problem of ambiguous standard terms. For example, there are a large number of industry-specific ambiguous terms in the evaluation standards. For example, the definition of "Level 3" varies significantly in different standards: CMMI DEV V2.0: Level 3 must meet 18 process areas (such as "Organizational Process Focus"); DCMM (Data Management Capability Maturity Model): Level 3 corresponds to the "Quantitative Management Level", requiring data management to achieve quantitative analysis; ISO / IEC 15504-5: Level 3 represents the "Defined Level", emphasizing the standardization of processes. For example, the standard versions are expressed in various forms (such as "GB / T 25000.51-2016" and "GB / T 25000.51-2021"). Existing methods have low accuracy when dealing with complex references such as "GB / T 25000.51-2016 (idt ISO 29110:2013)".

[0029] Figure 1 This is one of the flow charts of the contract text annotation method provided by the present invention, such as Figure 1 As shown, the method includes the following: Step 101: Obtain the contract text to be annotated.

[0030] Specifically, in the embodiment of the present application, the contract text to be marked is first obtained. Optionally, the contract text includes an evaluation contract text, a test contract text, a certification contract text, and a consulting contract text, etc., which are not limited in the embodiment of the present application. Optionally, the content to be marked in the contract text includes information related to the evaluation standards CMMM\ITSS\DCMM, such as the basic elements of the contract, Party A and Party B of the contract, the contract amount, the contract terms, the evaluation standards met by the contract, the grade, and the scope of application. Optionally, the evaluation standards include CMMM\ITSS\DCMM, and may also include other evaluation annotations, which are not specifically limited in the embodiment of the present application.

[0031] Step 102: Input the contract text to be annotated into the annotation model and output the annotation result of the contract text; the annotation model is used to identify the evaluation standard related information in the contract text and annotate the contract text.

[0032] Specifically, after obtaining the contract text to be annotated, the embodiment of the present application inputs the contract text to be annotated into the annotation model, and can quickly and accurately identify the evaluation standard related information in the contract text through the annotation model, and can also efficiently and accurately realize the annotation of the contract text, thereby improving the efficiency and accuracy of the contract text annotation, and effectively solving the low efficiency and error-prone problems in the related technology when relying on manual contract annotation.

[0033] For example, machine learning algorithms or deep learning frameworks can be used to train annotated datasets to generate contract annotation models tailored to specific needs. The trained annotation model can then be used to automatically annotate new evaluation contract texts, outputting structured data containing basic information, corresponding standards, evaluation levels, and requirements, enabling accurate and efficient annotation of contract texts.

[0034] The method of the above embodiment, by inputting the contract text to be annotated into the annotation model, can quickly and accurately identify the evaluation standard related information in the contract text through the annotation model, and can also realize the annotation of the contract text efficiently and accurately, thereby improving the efficiency and accuracy of the contract text annotation, and effectively solving the low efficiency and error-prone problems existing in the related technology when relying on manual contract annotation.

[0035] In some embodiments, the annotation model includes: The first annotation sub-model; wherein, The first annotation sub-model is used to obtain image information corresponding to the contract text, identify information related to the evaluation criteria from the image information, and perform annotation.

[0036] Specifically, the annotation model in the embodiment of the present application includes a first annotation sub-model, which is used to realize multimodal structured parsing of the contract text. Optionally, the first annotation sub-model can identify the evaluation standard related information from the image information corresponding to the contract text, so that the contract text can be annotated efficiently and accurately, thereby improving the efficiency and accuracy of the contract text annotation. Optionally, the first annotation sub-model can extract key features from the pre-processed multimodal information based on natural language processing (NLP) technology, such as the basic information of the contract (Party A and Party B, contract term, etc.), standard terms, evaluation level (such as maturity level three), etc., so as to realize accurate and efficient annotation of the contract text. Optionally, the preprocessing of the text includes scanning, extraction, cleaning, word segmentation and other preprocessing operations on the uploaded contract text, and may also include other preprocessing operations, which are not specifically limited in the embodiment of the present application.

[0037] For example, in this application, a knowledge graph can be constructed, integrating standard libraries such as ISO, IEEE, and GB. A BERT-CRF model can be used to identify standard names (e.g., "ISO / IEC 27001"), version numbers (e.g., "2022 Edition"), and corresponding clauses (e.g., "Article 6.1.3"). Alternatively, a rule-based state machine can be designed to parse hierarchical expressions such as "Maturity Level 3" and "Level 4," combining contextual semantic verification.

[0038] In the method of the above embodiment, the first annotation sub-model identifies information related to the evaluation criteria from the image information corresponding to the contract text, thereby achieving accurate and efficient annotation of the contract text and improving the efficiency and accuracy of contract text annotation.

[0039] In some embodiments, the annotation model further includes: The second annotation sub-model; wherein, The second annotation sub-model is used to match and annotate the evaluation criteria-related information from the contract text based on a preset regular expression.

[0040] Specifically, the embodiment of the present application can identify and annotate the evaluation standard related information in the contract text based on the standard matching rules. Optionally, the annotation model in the embodiment of the present application also includes a second annotation sub-model, which is used to match the evaluation standard related information from the contract text based on a preset regular expression and annotate it, so that the present application can not only identify and annotate the evaluation standard related information based on the multimodal information of the text contract, but also identify and annotate the evaluation standard related information based on the matching of regular expressions, making the annotation method of the contract text more flexible and diverse, and effectively improving the efficiency and accuracy of the contract text annotation. In addition, it should be noted that the efficiency of identifying and annotating the evaluation standard related information through regular expressions is significantly higher than the efficiency of identifying and annotating the evaluation standard related information through the multimodal information of the text contract, and can improve the comprehensiveness and accuracy of the recognition results, and achieve accurate and efficient annotation of the contract text.

[0041] For example, a regular expression template can be preset (such as "GB / T \d {4}-\d {4}" to match national standards) and combined with WordNet synonym expansion to improve generalization capabilities. This allows for quick and accurate matching of evaluation standard-related information from contract texts through standard matching rules and annotation, improving the efficiency and accuracy of contract text annotation.

[0042] The method of the above embodiment can not only identify and annotate information related to the evaluation criteria through the multimodal information of the text contract, but also identify and annotate information related to the evaluation criteria based on the matching of regular expressions, making the annotation method of the contract text more flexible and diverse, and effectively improving the efficiency and accuracy of the contract text annotation.

[0043] In some embodiments, the second annotation sub-model is further used to: Perform semantic transformation based on fuzzy logic to identify and annotate information related to evaluation criteria in the contract text.

[0044] Specifically, the embodiment of the present application can identify and annotate the evaluation standard related information in the contract text based on the inference rules. Optionally, semantic transformations such as "basic compliance → level 2" and "partial compliance → level 3" can be implemented based on fuzzy logic, thereby identifying and annotating the evaluation standard related information in the contract text. Optionally, the present application can identify and annotate the evaluation standard related information in the contract text based on the standard matching rules or inference rules of the second annotation sub-model when the first annotation sub-model cannot identify the evaluation standard related information in the contract text; it can also identify and annotate the evaluation standard related information in the contract text based on the standard matching rules and inference rules in the first annotation sub-model and the second annotation sub-model at the same time, thereby making the annotation method of the contract text more flexible and diverse, and effectively improving the efficiency and accuracy of the contract text annotation.

[0045] The method of the above embodiment performs semantic transformation based on fuzzy logic, identifies and annotates the evaluation criteria related information in the contract text, realizes the accurate identification and annotation of the evaluation criteria related information in the contract text based on inference rules, and also makes the annotation method of the contract text more flexible and diverse, effectively improving the efficiency and accuracy of contract text annotation.

[0046] In some embodiments, the second annotation sub-model is further used to: Based on syntactic analysis, target sentence patterns in the contract text that are relevant to the evaluation criteria are identified; and the contract text is annotated based on the content of the target sentence patterns.

[0047] Specifically, embodiments of this application also identify and annotate information related to evaluation criteria within contract texts based on association derivation. Alternatively, syntactic analysis can be used to identify target sentence patterns such as "According to... standard, clause..., achieve... level" and construct triples (standard, clause, level), thereby accurately identifying and annotating information related to evaluation criteria within contract texts.

[0048] The method of the above embodiment realizes the accurate identification and annotation of the evaluation standard related information in the contract text based on the association relationship deduction method, making the annotation method of the contract text more flexible and diverse, and effectively improving the efficiency and accuracy of the contract text annotation.

[0049] In some embodiments, the contract marking method further includes: Build the target operation interface; the target operation interface supports uploading contract documents, checking annotation results and adjusting annotation parameters.

[0050] Specifically, in an embodiment of the present application, an intuitive and easy-to-use operating interface is provided that supports users in uploading contract documents, viewing annotation results, and allowing users to adjust annotation parameters as needed, thereby achieving efficient interaction with users, better meeting users' contract text annotation needs, and improving the accuracy of contract annotation.

[0051] For example, Figure 2 As shown, the embodiment of the present application also provides a contract text annotation method that can automatically identify and annotate the basic information, evaluation standards, evaluation levels and evaluation requirements in the contract, thereby improving the efficiency of contract management and analysis. The specific process is as follows: (1) Text preprocessing: Perform preprocessing operations such as cleaning and word segmentation on the uploaded evaluation contract text for subsequent analysis.

[0052] (2) Feature extraction: Based on natural language processing (NLP) technology, key features are extracted from the preprocessed text, such as basic contract information (Party A and Party B, contract term, etc.), standard terms, and assessment level (such as maturity level 3).

[0053] (a) Multimodal structured analysis Standard terminology recognition: Build a domain knowledge graph, integrate ISO, IEEE, GB and other standard libraries, and use the BERT-CRF model to identify standard names (such as "ISO / IEC 27001"), version numbers (such as "2022 Edition") and corresponding clauses (such as "Article 6.1.3").

[0054] Assessment level extraction: Design a rule-based state machine to parse hierarchical expressions such as "Maturity Level 3" and "Level 4", and combine it with contextual semantic verification (such as "Compliant with CMMI DEV V2.0 Level 3 requirements").

[0055] Alternatively, a multimodal standardization algorithm can be constructed to build a domain knowledge graph encompassing terms from multiple evaluation standards (CMMM, ITSS, DCMM, etc.), using a BERT-ERNIE joint model to disambiguate standard terminology (e.g., distinguishing between CMMI Level 3 and DCMM Level 3). Alternatively, a graph convolutional network algorithm can be used to achieve cross-modal alignment of table cells and text terms.

[0056] (b) Dynamic rule engine construction Standard matching rules: Preset regular expression templates (such as "GB / T \d {4}-\d {4}" matches national standards) and combine WordNet synonym expansion to improve generalization capabilities.

[0057] Level reasoning rules: Based on fuzzy logic, semantic transformations such as "basic compliance → Level 2" and "partial compliance → Level 3" are implemented, and custom scoring weight configuration is supported.

[0058] Derivation of association relationships: Dependency parsing is used to identify sentences such as "According to... standard, article... reaches... level" and construct triples (standard, article, level).

[0059] Optionally, a dynamic rule engine can be designed to annotate contract texts based on intelligent matching and fuzzy logic reasoning. This hybrid matching strategy, based on regular expressions and semantic templates, supports the identification of complex references to international, national, and industry standards. Transformation rules can also be established, including rule base settings, supporting custom weighting (e.g., technical indicators accounting for 60%).

[0060] (3) Model training: Use machine learning algorithms or deep learning frameworks to train labeled data sets to build an evaluation contract annotation model that suits specific needs.

[0061] (4) Automated annotation: Use the trained model to automatically annotate the new evaluation contract text and output structured data containing basic information, corresponding standards, evaluation levels and their requirements.

[0062] Optionally, interpretable annotation and semantic association can be performed. Based on the attention mechanism and dependency syntax analysis, the decision basis of the model (such as feature importance weight) can be visualized to help users understand the annotation logic.

[0063] Semantically associate contract terms with external standard libraries (such as ISO specifications, legal provisions, and national standards) to ensure consistency between annotation content and industry requirements.

[0064] (5) User interaction interface: Provides an intuitive and easy-to-use operation interface that supports users to upload contract documents, view annotation results, and allow users to adjust annotation parameters as needed.

[0065] The method of the above embodiment provides an efficient and reliable annotation solution for the automated processing of contract texts, and can be widely used in contract risk management and compliance review in the fields of finance, law, and evaluation. The contract annotation method in the embodiment of this application has multiple advantages, including efficiency, accuracy, consistency, and scalability. Through automated annotation, the efficiency of contract text processing can be greatly improved. By combining deep learning and semantic annotation technology, the accuracy of the annotation results can be effectively ensured. By unifying the annotation rules, the subjective differences caused by manual annotation can be avoided. Moreover, the system supports the expansion of multiple contract types and evaluation standards.

[0066] The following describes the contract text annotation device provided by the present invention. The contract text annotation device described below and the contract text annotation method described above can be used for reference. Figure 3 As shown, including: An acquisition module 310 is used to acquire the contract text to be annotated; The annotation module 320 is used to input the contract text to be annotated into the annotation model and output the annotation result of the contract text; the annotation model is used to identify the information related to the evaluation criteria in the contract text and annotate the contract text.

[0067] Optionally, the annotation model includes: The first annotation sub-model; wherein, The first annotation sub-model is used to obtain image information corresponding to the contract text, identify information related to the evaluation criteria from the image information, and annotate it.

[0068] Optionally, the annotation model also includes: The second annotation sub-model; wherein, The second annotation sub-model is used to match and annotate information related to the evaluation criteria from the contract text based on a preset regular expression.

[0069] Optionally, the second annotation sub-model is further used to: Based on fuzzy logic, semantic transformation is performed to identify and annotate information related to the evaluation criteria in the contract text.

[0070] Optionally, the second annotation sub-model is further used to: Based on syntactic analysis, target sentence patterns in the contract text that are relevant to the evaluation criteria are identified; and the contract text is annotated based on the content of the target sentence patterns.

[0071] Optionally, the device further includes a construction module; the construction module is used to construct a target operation interface; the target operation interface supports uploading of contract documents, viewing of annotation results, and adjustment of annotation parameters.

[0072] Figure 4The following illustrates a physical structure diagram of an electronic device, which may include a processor 410, a communications interface 420, a memory 430, and a communications bus 440. Processor 410, communications interface 420, and memory 430 communicate with each other via communications bus 440. Processor 410 may invoke logic instructions in memory 430 to execute a contract text annotation method, which includes: obtaining a contract text to be annotated; inputting the contract text to be annotated into an annotation model and outputting the annotation results of the contract text; the annotation model is used to identify information related to the evaluation criteria in the contract text and annotate the contract text.

[0073] Furthermore, the logic instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product, stored in a storage medium, includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0074] On the other hand, the present invention also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the contract text annotation method provided by the above methods, which includes: obtaining the contract text to be annotated; inputting the contract text to be annotated into the annotation model, and outputting the annotation result of the contract text; the annotation model is used to identify information related to the evaluation criteria in the contract text and annotate the contract text.

[0075] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, it is implemented to execute the contract text annotation method provided by the above methods, the method including: obtaining the contract text to be annotated; inputting the contract text to be annotated into the annotation model, and outputting the annotation result of the contract text; the annotation model is used to identify information related to the evaluation criteria in the contract text and annotate the contract text.

[0076] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0077] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0078] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for marking a contract text, characterized in that: include: Get the contract text to be annotated; Inputting the contract text to be annotated into the annotation model, and outputting the annotation result of the contract text; The annotation model is used to identify the evaluation criteria related information in the contract text and to annotate the contract text.

2. The method for marking a contract text according to claim 1, characterized in that: The annotation model includes: The first annotation sub-model; wherein, The first annotation sub-model is used to obtain image information corresponding to the contract text, identify information related to the evaluation criteria from the image information, and perform annotation.

3. The method for marking a contract text according to claim 2, characterized in that: The annotation model also includes: The second annotation sub-model; wherein, The second annotation sub-model is used to match and annotate information related to the evaluation criteria from the contract text based on a preset regular expression.

4. The method for marking a contract text according to claim 3, characterized in that: The second annotation sub-model is further used to: Semantic transformation is performed based on fuzzy logic to identify and annotate the evaluation criteria-related information in the contract text.

5. The method for marking a contract text according to claim 4, characterized in that: The second annotation sub-model is further used to: Based on syntactic analysis, target sentence patterns in the contract text that are relevant to the evaluation criteria are identified; and the contract text is annotated based on the content of the target sentence patterns.

6. The method for marking a contract text according to any one of claims 1 to 5, characterized in that: The method further comprises: Construct a target operation interface; the target operation interface supports uploading contract documents, viewing annotation results, and adjusting annotation parameters.

7. A contract text annotation device, characterized in that: include: The acquisition module is used to obtain the contract text to be annotated; The annotation module is used to input the contract text to be annotated into the annotation model and output the annotation result of the contract text; the annotation model is used to identify the evaluation standard related information in the contract text and annotate the contract text.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method for marking the contract text as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for marking a contract text as described in any one of claims 1 to 6 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method for marking a contract text as described in any one of claims 1 to 6 is implemented.

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