CN110765770A - Automatic contract generation method and device - Google Patents
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Abstract
The embodiment of the invention provides a method and a device for automatically generating a contract, which relate to the technical field of pedestal operation and maintenance, and comprise the following steps: acquiring a contract generation request, wherein the contract generation request carries basic information of a contract to be generated, and the basic information comprises a contract name and a type to which contract business belongs; calling a contract template according to the basic information of the contract to be generated, wherein the contract template comprises a plurality of contract element filling fields; acquiring contract element values input by a user in a plurality of contract element filling domains; generating a target contract according to the contract template and the contract element value; comparing the risk of the target contract with a contract model prestored in a database to obtain risk prompt information of the target contract; and outputting the target contract containing the risk prompt information. The technical scheme provided by the embodiment of the invention can solve the problem of low contract making efficiency in the prior art.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to the technical field of pedestal operation and maintenance, in particular to a method and a device for automatically generating a contract.
[ background of the invention ]
At present, more and more contracts are needed in enterprises, different types of contracts have different contract contents, the same type of contracts also have different contract contents due to personalized agreements, potential risks of the contracts are difficult to know in time in the generation process of the various types of contracts, the manufacturing, auditing and modifying work is heavy, and a large amount of manpower and material resources are wasted.
[ summary of the invention ]
In view of this, embodiments of the present invention provide a method and an apparatus for automatically generating a contract, so as to solve the problem of low contract making efficiency in the prior art.
In order to achieve the above object, according to one aspect of the present invention, there is provided an automatic contract generation method, including: acquiring a contract generation request, wherein the contract generation request carries basic information of a contract to be generated, and the basic information comprises a contract name and a type to which contract business belongs; calling a contract template according to the basic information of the contract to be generated, wherein the contract template comprises a plurality of contract element filling fields; acquiring contract element values input by a user in the plurality of contract element filling domains; generating a target contract according to the contract template and the contract element values; comparing the target contract with a contract model prestored in a database to obtain risk prompt information of the target contract; and outputting the target contract containing the risk prompt information.
Further, the calling of the contract template according to the basic information of the contract to be generated includes: calling a contract template set according to the type of the service of the contract to be generated, wherein the contract template set comprises a plurality of contract templates, and each contract template is associated with a corresponding contract name; acquiring a contract template matched with the contract name of the contract to be generated from the contract template set; outputting a plurality of contract element fill fields in the contract template.
Further, the calling of the contract template according to the basic information of the contract to be generated includes: extracting key words from the basic information, and searching a plurality of contract samples in a network search engine according to the key words; de-duplicating the plurality of contract samples; training a contract template generation model based on a plurality of contract samples after the duplicate removal processing, wherein the contract template generation model is obtained by performing supervised training on an existing convolutional neural network structure by using a machine learning method and the contract samples; and obtaining a contract template output by the trained contract template generation model, wherein the contract template comprises a plurality of contract element filling fields.
Further, the risk comparing the target contract with a contract model pre-stored in a database to obtain the risk prompt information of the target contract includes:
calling a contract template consistent with the business affiliated type and contract name of the target contract according to the basic information of the target contract, wherein a clause text in the contract template is associated with corresponding risk prompt information; dividing the target contract into a plurality of sub-segment texts, and calculating semantic similarity scores of each sub-segment text and a clause text in the contract template through a similarity calculation model; taking risk prompt information corresponding to the clause text with the highest semantic similarity score as risk prompt information of the sub-segment text; and marking the risk prompt information on the corresponding sub-section text of the target contract.
Further, after the outputting the target contract containing the risk hint information, the method further comprises: extracting keywords in the risk prompt information, and obtaining the risk grade according to the keywords; and marking the target contract according to the risk level and the corresponding marking color thereof so as to facilitate the user to modify according to the marked target contract, wherein the modification mode comprises at least one of re-editing, deleting, replacing and adjusting the word order.
Further, after the outputting the target contract containing the risk prompt information, the method further comprises: responding to an auditing completion indication of the user, and acquiring a seal identifier in a contract template according to the contract template called by the target contract; calling an interface of a seal system, and acquiring seal information corresponding to the seal identification; determining a stamping position corresponding to the stamp information in the target contract according to the stamping position information in the contract template; and outputting the target contract after stamping the seal information to the corresponding stamping position in the target contract.
In order to achieve the above object, according to one aspect of the present invention, there is provided an automatic contract generation apparatus including: the first acquisition unit is used for acquiring a contract generation request, wherein the contract generation request carries basic information of a contract to be generated, and the basic information comprises a contract name and a type to which a contract service belongs; the calling unit is used for calling a contract template according to the basic information of the contract to be generated, and the contract template comprises a plurality of contract element filling fields; a second acquisition unit configured to acquire contract element values input by a user within the plurality of contract element population fields; the generating unit is used for generating a target contract according to the contract template and the contract element value; the comparison unit is used for carrying out risk comparison on the target contract and a contract model book prestored in a database to obtain risk prompt information of the target contract; and the output unit is used for outputting the target contract containing the risk prompt information.
Further, the retrieval unit includes: the transfer subunit is configured to transfer a contract template set according to a type to which the service of the contract to be generated belongs, where the contract template set includes a plurality of contract templates, and each contract template is associated with a corresponding contract name; the first acquiring subunit is used for acquiring a contract template matched with the contract name of the contract to be generated from the contract template set; and the output subunit is used for outputting the plurality of contract element filling fields in the contract template.
In order to achieve the above object, according to one aspect of the present invention, there is provided a computer nonvolatile storage medium including a stored program that, when executed, controls an apparatus on which the storage medium is located to execute the above contract automatic generation method.
In order to achieve the above object, according to one aspect of the present invention, there is provided a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the contract automatic generation method described above when executing the computer program.
In the scheme, a contract template is called through basic information of a contract to be generated, and a target contract is generated through contract element values input by a user in a filling domain; comparing the target contract with a contract model prestored in a database to obtain risk prompt information of the target contract; and generating a target contract containing the risk prompt information, improving the contract generation efficiency and simultaneously enabling the user to be clear of the risk of the contract.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
FIG. 1 is a flow chart of an alternative automatic contract generation method provided by an embodiment of the present invention;
FIG. 2 is a schematic diagram of an alternative automatic contract generation apparatus provided by an embodiment of the present invention;
fig. 3 is a schematic diagram of an alternative computer device provided by the embodiment of the present invention.
[ detailed description ] embodiments
For better understanding of the technical solutions of the present invention, the following detailed descriptions of the embodiments of the present invention are provided with reference to the accompanying drawings.
It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be understood that the term "and/or" as used herein is merely one type of association that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
It should be understood that although the terms first, second, third, etc. may be used to describe the terminals in the embodiments of the present invention, the terminals should not be limited by these terms. These terms are only used to distinguish one terminal from another. For example, a first terminal may also be referred to as a second terminal, and similarly, a second terminal may also be referred to as a first terminal, without departing from the scope of embodiments of the present invention.
The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrases "if determined" or "if detected (a stated condition or event)" may be interpreted as "when determined" or "in response to a determination" or "when detected (a stated condition or event)" or "in response to a detection (a stated condition or event)", depending on the context.
Fig. 1 is a flowchart of an automatic contract generation method according to an embodiment of the present invention, as shown in fig. 1, the method includes:
step S101, a contract generation request is obtained, the contract generation request carries basic information of a contract to be generated, and the basic information comprises a contract name and a type of contract business.
The name of the contract can be, for example, a funding contract, an shareholder contract, an equity transfer contract, a house lease contract, a house buying and selling contract, a bond transfer agreement, and the like; the type of the business comprises any one of banking business, trust business, securities business and fund business. It will be appreciated that the user may select the desired service type and the desired contract name on a preset web page.
And S102, calling a contract template according to the basic information of the contract to be generated, wherein the contract template comprises a plurality of contract element filling domains. As will be appreciated, a "fill field" refers to an editable, filled-in area that is pre-inserted into the contract template.
In step S103, contract element values input by the user in the plurality of contract element filling fields are acquired. The contractual elements may be the contract's bid, the number of contracts, the amount or consideration contracted by the contract, the duration of contract performance, the location and manner, the liability of breach, the measures to resolve disputes, etc. Illustratively, the contract element fill fields include borrower name, borrower nature, borrowing usage, borrowing period, presence or absence of guarantee, placement mode, dispute resolution mode, and the like. Further, the fill field can be filled or edited in various ways, such as text filling, number filling, preset field selection, and the like. For example, the borrowing period can be directly input by the user through editing for 30 years, or preset 30 years can be selected through clicking, so that the contract generation efficiency is improved.
And step S104, generating the target contract according to the contract template and the contract element value.
In this embodiment, the contract element filling domain is provided with a preset identifier, and the server can directly associate the contract element value with the corresponding contract element filling domain through the identifier, thereby ensuring the accuracy of the generated target contract.
And step S105, carrying out risk comparison on the target contract and a contract model book prestored in a database to obtain risk prompt information of the target contract.
And step S106, outputting the target contract containing the risk prompt information.
In the scheme, a contract template is called through basic information of a contract to be generated, and a target contract is generated through contract element values input by a user in a filling domain; comparing the risk of the target contract with a contract model prestored in a database to obtain risk prompt information of the target contract; and generating a target contract containing risk prompt information, improving contract generation efficiency and simultaneously enabling a user to be clear of risks in the contract.
Optionally, the invoking of the contract template according to the basic information of the contract to be generated includes: calling a contract template set according to the type of the service of the contract to be generated, wherein the contract template set comprises a plurality of contract templates, and each contract template is associated with one corresponding contract name; acquiring a contract template matched with the contract name of a contract to be generated from the contract template set; outputting a plurality of contract element fill fields in the contract template.
It can be understood that the server parses the contract name and the type of the contract service in the basic information, primarily screens the contract template set according to the type of the service, and then matches the contract name in the primarily screened contract template set to determine the required contract template.
Optionally, the invoking of the contract template according to the basic information of the contract to be generated includes: extracting key words from the basic information, and searching a plurality of contract samples in a network search engine according to the key words; carrying out deduplication processing on a plurality of contract samples; training a contract template generation model based on the plurality of contract samples subjected to the duplicate removal processing; and obtaining a contract template output by the trained contract template generation model, wherein the contract template comprises a plurality of contract element filling fields.
Specifically, the multiple contract samples are subjected to deduplication processing by adopting a local sensitive hash (simHash) algorithm, a small number of character strings in the contract samples are extracted by using the same rule to represent the whole contract sample, and if the coincidence degree of the small number of character strings is high, the repetition degree of the whole contract sample is also high. It can be understood that similar texts and corresponding simHash strings are also similar, that is, the similarity of the simHash signature values of two texts intuitively reflects the similarity of the original texts, which makes text deduplication possible. After the text to be de-duplicated is mapped by the simHash algorithm, 01 character strings can be obtained, and if the 01 character strings of the two texts are different in 0 and 1 at a few positions, the other most positions are completely consistent. Then the similarity of the two texts is extremely high. Thus, by counting the number of positions where 0 or 1 differs between two 01 strings, the resulting value can be used to characterize the similarity between two texts.
The contract template generation model is obtained by performing supervised training on the existing convolutional neural network structure by using a machine learning method and a contract sample. In one embodiment, the contract template generation model is a model formed by a recurrent neural network, but in other embodiments, a network model such as a convolutional neural network or a countermeasure network may be used. By learning the characteristics of the composition elements, semantic relation classification and the like of the contract in the contract sample, the model can generate a required contract template.
Optionally, the risk comparing the target contract with a contract template prestored in the database to obtain risk prompt information of the target contract includes:
calling a contract template consistent with the business affiliated type and the contract name of the target contract according to the basic information of the target contract, wherein a clause text in the contract template is associated with corresponding risk prompt information; dividing the target contract into a plurality of sub-segment texts, and calculating semantic similarity scores of each sub-segment text and a clause text in the contract template through a similarity calculation model; taking risk prompt information corresponding to the clause text with the highest semantic similarity score as risk prompt information of the sub-segment text; and marking the risk prompt information on the corresponding sub-section text of the target contract.
In the present embodiment, the similarity calculation model is used to determine whether two texts are similar texts. Specifically, the similarity calculation model may determine whether the two texts are similar texts based on the similarity parameter by obtaining the similarity parameter between the two texts. The similarity parameter comprises at least one of Jaccard coefficient, editing distance and semantic distance.
The Jaccard coefficient is used for comparing similarity and difference between limited sample sets, specifically, words of texts to be compared can be segmented to obtain two phrase sets, and then text similarity is obtained based on the two phrase sets.
The edit distance is a levenstein distance, which can be a measure of similarity between two texts. Illustratively, the edit distance between two strings is the minimum number of operations required to convert one string into another string, and the operations are limited to three types: for insertion, deletion or replacement of a character.
The semantic distance measures the similarity between two texts from the semantic angle, the semantic distance between the two texts can be calculated by adopting a Word2Vec method, the texts to be compared are converted into an expression form of a semantic level, and then the semantic distance between the two texts is calculated by various distance representation methods.
In this embodiment, the risk prompt message includes legal terms and risk correction suggestions according to the risk. Therefore, the user can modify the target contract after seeing the risk prompt information.
Optionally, after outputting the target contract with the risk prompt information, the method further includes: extracting keywords in the risk prompt information, and obtaining a risk grade according to the keywords; and marking the target contract according to the risk level and the corresponding marking color thereof so as to facilitate the user to modify according to the marked target contract, wherein the modification mode comprises at least one of re-editing, deleting, replacing and adjusting the language order.
Illustratively, for example, the extracted keyword is "about", which is a forbidden word in the contract and is labeled with red, so that the user can modify the word conveniently, and the stricter vocabulary of the contract is eliminated, so that the target contract is more standard and accurate.
Optionally, after outputting the target contract with the risk prompt information, the method further includes: responding to an auditing completion indication of a user, and acquiring a seal identifier in a contract template according to the contract template called by a target contract; calling an interface of the seal system, and acquiring seal information corresponding to the seal identification; determining a stamping position corresponding to the stamp information in the target contract according to the stamping position information in the contract template; and outputting the target contract after stamping the stamp information to the corresponding stamping position in the target contract.
After the user finishes auditing, the server can call corresponding seal information according to the seal identification in the contract template, and then the seal information is stamped to the corresponding position of the target contract according to the coordinate value of the seal in the contract template, so that an effective contract is generated quickly and effectively, and the contract making efficiency is improved.
An embodiment of the present invention provides an automatic contract generation apparatus, configured to execute the automatic contract generation method described above, and as shown in fig. 2, the apparatus includes: the device comprises a first acquisition unit 10, a calling unit 20, a second acquisition unit 30, a generation unit 40, a comparison unit 50 and an output unit 60.
The first obtaining unit 10 is configured to obtain a contract generating request, where the contract generating request carries basic information of a contract to be generated, and the basic information includes a contract name and a type to which a contract service belongs.
The name of the contract can be, for example, a funding contract, an shareholder contract, an equity transfer contract, a house lease contract, a house buying and selling contract, a bond transfer agreement, and the like; the type of the business comprises any one of banking business, trust business, securities business and fund business. It will be appreciated that the user may select the desired service type and the desired contract name on a preset web page.
And the invoking unit 20 is used for invoking a contract template according to the basic information of the contract to be generated, wherein the contract template comprises a plurality of contract element filling fields. As will be appreciated, a "fill field" refers to an editable, filled-in area that is pre-inserted into the contract template.
A second acquiring unit 30, configured to acquire contract element values input by the user within the plurality of contract element filling fields. The contractual elements may be the contract's bid, the number of contracts, the amount or consideration contracted by the contract, the duration of contract performance, the location and manner, the liability of breach, the measures to resolve disputes, etc. Illustratively, the contract element fill fields include borrower name, borrower nature, borrowing usage, borrowing period, presence or absence of guarantee, placement mode, dispute resolution mode, and the like. Further, the fill field can be filled or edited in various ways, such as text filling, number filling, preset field selection, and the like. For example, the borrowing period can be directly input by the user through editing for 30 years, or preset 30 years can be selected through clicking, so that the contract generation efficiency is improved.
And the generating unit 40 is used for generating the target contract according to the contract template and the contract element value.
In this embodiment, the contract element filling domain is provided with a preset identifier, and the server can directly associate the contract element value with the corresponding contract element filling domain through the identifier, thereby ensuring the accuracy of the generated target contract.
And the comparison unit 50 is used for performing risk comparison on the target contract and a contract model book prestored in the database to obtain risk prompt information of the target contract.
And the output unit 60 is used for outputting the target contract containing the risk prompt information.
In the scheme, a contract template is called through basic information of a contract to be generated, and a target contract is generated through contract element values input by a user in a filling domain; comparing the risk of the target contract with a contract model prestored in a database to obtain risk prompt information of the target contract; and generating a target contract containing risk prompt information, improving contract generation efficiency and simultaneously enabling a user to be clear of risks in the contract.
Optionally, the invoking of the contract template according to the basic information of the contract to be generated includes: calling a contract template set according to the type of the service of the contract to be generated, wherein the contract template set comprises a plurality of contract templates, and each contract template is associated with one corresponding contract name; acquiring a contract template matched with the contract name of a contract to be generated from the contract template set; outputting a plurality of contract element fill fields in the contract template.
It can be understood that the server parses the contract name and the type of the contract service in the basic information, primarily screens the contract template set according to the type of the service, and then matches the contract name in the primarily screened contract template set to determine the required contract template.
Further, the retrieving unit 20 includes a retrieving subunit, a first obtaining subunit, and an output subunit.
The contract template set comprises a plurality of contract templates, wherein each contract template is associated with a corresponding contract name; the first acquiring subunit is used for acquiring a contract template matched with the contract name of the contract to be generated from the contract template set; and the output subunit is used for outputting the plurality of contract element filling fields in the contract template.
Optionally, the invoking subunit is configured to extract a keyword from the basic information, and search a plurality of contract samples in a web search engine according to the keyword; carrying out deduplication processing on a plurality of contract samples; training a contract template generation model based on the plurality of contract samples subjected to the duplicate removal processing; and obtaining a contract template output by the trained contract template generation model, wherein the contract template comprises a plurality of contract element filling fields.
Specifically, the deduplication processing of multiple contract samples may adopt a locality sensitive hashing algorithm, and a small number of character strings in the contract samples are extracted by using the same rule to represent the whole contract sample, and if the coincidence degree of the small number of character strings is high, the repetition degree of the whole contract sample is also high. It can be understood that similar texts and corresponding simHash strings are also similar, that is, the similarity of the simHash signature values of two texts intuitively reflects the similarity of the original texts, which makes text deduplication possible. After the text to be de-duplicated is mapped by the simHash algorithm, 01 character strings can be obtained, and if the 01 character strings of the two texts are different in 0 and 1 at a few positions, the other most positions are completely consistent. Then the similarity of the two texts is extremely high. Thus, by counting the number of positions where 0 or 1 differs between two 01 strings, the resulting value can be used to characterize the similarity between two texts.
The contract template generation model is obtained by performing supervised training on the existing convolutional neural network structure by using a machine learning method and a contract sample. In one embodiment, the contract template generation model is a model formed by a recurrent neural network, but in other embodiments, a network model such as a convolutional neural network or a countermeasure network may be used. By learning the characteristics of the composition elements, semantic relation classification and the like of the contract in the contract sample, the model can generate a required contract template.
Optionally, the comparing unit 50 includes a second retrieving subunit, a dividing subunit, a confirming subunit and a labeling subunit.
The second calling subunit is used for calling a contract template consistent with the business affiliated type and the contract name of the target contract according to the basic information of the target contract, and the clause text in the contract template is associated with corresponding risk prompt information; the segmentation subunit is used for segmenting the target contract into a plurality of sub-segment texts, and calculating the semantic similarity score between each sub-segment text and the clause text in the contract template through a similarity calculation model; the confirming subunit is used for taking the risk prompt information corresponding to the clause text with the highest semantic similarity score as the risk prompt information of the sub-segment text; and the marking subunit is used for marking the risk prompt information on the corresponding sub-section text of the target contract.
In the present embodiment, the similarity calculation model is used to determine whether two texts are similar texts. Specifically, the similarity calculation model may determine whether the two texts are similar texts based on the similarity parameter by obtaining the similarity parameter between the two texts. The similarity parameter comprises at least one of Jaccard coefficient, editing distance and semantic distance.
The Jaccard coefficient is used for comparing similarity and difference between limited sample sets, specifically, words of texts to be compared can be segmented to obtain two phrase sets, and then text similarity is obtained based on the two phrase sets.
The edit distance is a levenstein distance, which can be a measure of similarity between two texts. Illustratively, the edit distance between two strings is the minimum number of operations required to convert one string into another string, and the operations are limited to three types: for insertion, deletion or replacement of a character.
The semantic distance measures the similarity between two texts from the semantic angle, the semantic distance between the two texts can be calculated by adopting a Word2Vec method, the texts to be compared are converted into an expression form of a semantic level, and then the semantic distance between the two texts is calculated by various distance representation methods.
In this embodiment, the risk prompt message includes legal terms and risk correction suggestions according to the risk. Therefore, the user can modify the target contract after seeing the risk prompt information.
Optionally, the device further comprises an extraction unit and a labeling unit.
The extracting unit is used for extracting the keywords in the risk prompt information and obtaining the risk grade according to the keywords; and the marking unit is used for marking the target contract according to the risk level and the corresponding marking color thereof so as to facilitate the user to modify according to the marked target contract, wherein the modification mode comprises at least one of re-editing, deleting, replacing and adjusting the word sequence.
Illustratively, for example, the extracted keyword is "about", which is a forbidden word in the contract and is labeled with red, so that the user can modify the word conveniently, and the stricter vocabulary of the contract is eliminated, so that the target contract is more standard and accurate.
Optionally, the apparatus further includes a third obtaining unit, a calling unit, a determining unit, and a second output unit.
The third acquisition unit is used for responding to an audit completion instruction of a user and acquiring a seal identifier in a contract template according to the contract template called by a target contract; the calling unit is used for calling an interface of the seal system and acquiring seal information corresponding to the seal identification; the determining unit is used for determining a stamping position corresponding to the stamp information in the target contract according to the stamping position information in the contract template; and the second output unit is used for outputting the target contract after the seal information is stamped to the corresponding stamping position in the target contract.
After the user finishes auditing, the server can call corresponding seal information according to the seal identification in the contract template, and then the seal information is stamped to the corresponding position of the target contract according to the coordinate value of the seal in the contract template, so that an effective contract is generated quickly and effectively, and the contract making efficiency is improved.
The embodiment of the invention provides a non-volatile storage medium of a computer, wherein the storage medium comprises a stored program, and when the program runs, equipment where the storage medium is located is controlled to execute the following steps: acquiring a contract generation request, wherein the contract generation request carries basic information of a contract to be generated, and the basic information comprises a contract name and a type to which contract business belongs; calling a contract template according to the basic information of the contract to be generated, wherein the contract template comprises a plurality of contract element filling fields; acquiring contract element values input by a user in a plurality of contract element filling domains; generating a target contract according to the contract template and the contract element value; comparing the risk of the target contract with a contract model prestored in a database to obtain risk prompt information of the target contract; and outputting the target contract containing the risk prompt information.
Optionally, the program controls the apparatus in which the storage medium is located to perform the following steps when running: calling a contract template set according to the type of the service of the contract to be generated, wherein the contract template set comprises a plurality of contract templates, and each contract template is associated with one corresponding contract name; acquiring a contract template matched with the contract name of a contract to be generated from the contract template set; outputting a plurality of contract element fill fields in the contract template.
Optionally, the program controls the apparatus in which the storage medium is located to perform the following steps when running: extracting key words from the basic information, and searching a plurality of contract samples in a network search engine according to the key words; carrying out deduplication processing on a plurality of contract samples; training a contract template generation model based on a plurality of contract samples after the duplicate removal, wherein the contract template generation model is obtained by performing supervised training on the existing convolutional neural network structure by using a machine learning method and the contract samples; and obtaining the contract template output by the trained contract template generation model.
Optionally, the program controls the apparatus in which the storage medium is located to perform the following steps when running: calling a contract template consistent with the business affiliated type and the contract name of the target contract according to the basic information of the target contract, wherein a clause text in the contract template is associated with corresponding risk prompt information; dividing the target contract into a plurality of sub-segment texts, and calculating semantic similarity scores of each sub-segment text and a clause text in the contract template through a similarity calculation model; taking risk prompt information corresponding to the clause text with the highest semantic similarity score as risk prompt information of the sub-segment text; and marking the risk prompt information on the corresponding sub-section text of the target contract.
Optionally, the program controls the apparatus in which the storage medium is located to perform the following steps when running: extracting keywords in the risk prompt information, and obtaining a risk grade according to the keywords; and marking the target contract according to the risk level and the corresponding marking color thereof so as to facilitate the user to modify according to the marked target contract, wherein the modification mode comprises at least one of re-editing, deleting, replacing and adjusting the language order.
Optionally, the program controls the apparatus in which the storage medium is located to perform the following steps when running: responding to an auditing completion indication of a user, and acquiring a seal identifier of a contract template according to the contract template called by a target contract; calling an interface of the seal system, and acquiring seal information corresponding to the seal identification; determining a stamping position corresponding to the stamp information in the target contract according to the stamping position information in the contract template; and outputting the target contract after stamping the stamp information to the corresponding stamping position in the target contract.
Fig. 3 is a schematic diagram of a computer device according to an embodiment of the present invention. As shown in fig. 3, the computer apparatus 100 of this embodiment includes: the processor 101, the memory 102, and the computer program 103 stored in the memory 102 and capable of running on the processor 101, where the processor 101 implements the automatic contract generating method in the embodiment when executing the computer program 103, and in order to avoid repetition, details are not repeated here. Alternatively, the computer program is executed by the processor 101 to implement the functions of each model/unit in the contract automatic generation apparatus in the embodiment, which are not described herein again to avoid redundancy.
The computing device 100 may be a desktop computer, a notebook, a palm top computer, a cloud server, or other computing devices. The computer device may include, but is not limited to, a processor 101, a memory 102. Those skilled in the art will appreciate that fig. 3 is merely an example of a computing device 100 and is not intended to limit the computing device 100 and that it may include more or less components than those shown, or some of the components may be combined, or different components, e.g., the computing device may also include input output devices, network access devices, buses, etc.
The Processor 101 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 102 may be an internal storage unit of the computer device 100, such as a hard disk or a memory of the computer device 100. The memory 102 may also be an external storage device of the computer device 100, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc., provided on the computer device 100. Further, the memory 102 may also include both internal storage units and external storage devices of the computer device 100. The memory 102 is used for storing computer programs and other programs and data required by the computer device. The memory 102 may also be used to temporarily store data that has been output or is to be output.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions in actual implementation, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) or a Processor (Processor) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. An automatic contract generation method, characterized in that the method comprises:
acquiring a contract generation request, wherein the contract generation request carries basic information of a contract to be generated, and the basic information comprises a contract name and a type to which contract business belongs;
calling a contract template according to the basic information of the contract to be generated, wherein the contract template comprises a plurality of contract element filling fields;
acquiring contract element values input by a user in the plurality of contract element filling domains;
generating a target contract according to the contract template and the contract element values;
comparing the target contract with a contract model prestored in a database to obtain risk prompt information of the target contract;
and outputting the target contract containing the risk prompt information.
2. The method according to claim 1, wherein the invoking of the contract template according to the basic information of the contract to be generated comprises:
calling a contract template set according to the type of the service of the contract to be generated, wherein the contract template set comprises a plurality of contract templates, and each contract template is associated with a corresponding contract name;
acquiring a contract template matched with the contract name of the contract to be generated from the contract template set;
outputting a plurality of contract element fill fields in the contract template.
3. The method according to claim 1, wherein the invoking of the contract template according to the basic information of the contract to be generated comprises:
extracting key words from the basic information, and searching a plurality of contract samples in a network search engine according to the key words;
de-duplicating the plurality of contract samples;
training a contract template generation model based on a plurality of contract samples after the duplicate removal processing, wherein the contract template generation model is obtained by performing supervised training on an existing convolutional neural network structure by using a machine learning method and the contract samples;
and obtaining a contract template output by the trained contract template generation model, wherein the contract template comprises a plurality of contract element filling fields.
4. The method according to claim 1, wherein the risk comparing the target contract with a contract template pre-stored in a database to obtain risk prompt information of the target contract comprises:
calling a contract template consistent with the business affiliated type and contract name of the target contract according to the basic information of the target contract, wherein a clause text in the contract template is associated with corresponding risk prompt information;
dividing the target contract into a plurality of sub-segment texts, and calculating semantic similarity scores of each sub-segment text and a clause text in the contract template through a similarity calculation model;
taking risk prompt information corresponding to the clause text with the highest semantic similarity score as risk prompt information of the sub-segment text;
and marking the risk prompt information on the corresponding sub-section text of the target contract.
5. The method of claim 1, wherein after said outputting the target contract with the risk tip information, the method further comprises:
extracting keywords in the risk prompt information, and obtaining the risk grade according to the keywords;
and marking the target contract according to the risk level and the corresponding marking color thereof so as to facilitate the user to modify according to the marked target contract, wherein the modification mode comprises at least one of re-editing, deleting, replacing and adjusting the word order.
6. The method according to any one of claims 1 to 5, wherein after the outputting of the target contract containing the risk hint information, the method further comprises:
responding to an auditing completion indication of the user, and acquiring a seal identifier in a contract template according to the contract template called by the target contract;
calling an interface of a seal system, and acquiring seal information corresponding to the seal identification;
determining a stamping position corresponding to the stamp information in the target contract according to the stamping position information in the contract template;
and outputting the target contract after stamping the seal information to the corresponding stamping position in the target contract.
7. An apparatus for automatically generating a contract, the apparatus comprising:
the first acquisition unit is used for acquiring a contract generation request, wherein the contract generation request carries basic information of a contract to be generated, and the basic information comprises a contract name and a type to which a contract service belongs;
the calling unit is used for calling a contract template according to the basic information of the contract to be generated, and the contract template comprises a plurality of contract element filling fields;
a second acquisition unit configured to acquire contract element values input by a user within the plurality of contract element population fields;
the generating unit is used for generating a target contract according to the contract template and the contract element value;
the comparison unit is used for carrying out risk comparison on the target contract and a contract model book prestored in a database to obtain risk prompt information of the target contract;
and the output unit is used for outputting the target contract containing the risk prompt information.
8. The apparatus of claim 7, wherein the retrieving unit comprises:
the transfer subunit is configured to transfer a contract template set according to a type to which the service of the contract to be generated belongs, where the contract template set includes a plurality of contract templates, and each contract template is associated with a corresponding contract name;
the first acquiring subunit is used for acquiring a contract template matched with the contract name of the contract to be generated from the contract template set;
and the output subunit is used for outputting the plurality of contract element filling fields in the contract template.
9. A computer nonvolatile storage medium including a stored program, wherein when the program runs, a device on which the storage medium is installed is controlled to execute the contract automatic generation method according to any one of claims 1 to 6.
10. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the automatic contract generation method according to any one of claims 1 to 6 when executing the computer program.
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| CN201910830509.1A CN110765770B (en) | 2019-09-04 | 2019-09-04 | Automatic contract generation method and device |
| PCT/CN2019/117088 WO2021042521A1 (en) | 2019-09-04 | 2019-11-11 | Contract automatic generation method, computer device and computer non-volatile storage medium |
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| CN201910830509.1A CN110765770B (en) | 2019-09-04 | 2019-09-04 | Automatic contract generation method and device |
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| CN110765770B (en) | 2024-07-19 |
| WO2021042521A1 (en) | 2021-03-11 |
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