Method and device for determining legal event judgment information and electronic equipment

Abstract

The invention relates to the technical field of computers, and discloses a legal event judgment information determination method and device and electronic equipment, and the method comprises the steps: obtaining first event information corresponding to first question information; determining a plurality of preset texts associated with the first event information in a preset database based on the first event information; processing a first preset text in the plurality of preset texts to obtain a plurality of retrieval pairs corresponding to the first preset text; clustering the plurality of retrieval pairs corresponding to the first preset text to obtain a plurality of candidate seed retrieval pairs; determining a target confidence score of each candidate seed retrieval pair in the plurality of candidate seed retrieval pairs; determining the candidate seed retrieval pair with the target confidence score greater than or equal to a preset score in the plurality of candidate seed retrieval pairs as a target seed retrieval pair; and determining the retrieval identifier and the retrieval content corresponding to the target seed retrieval pair as event judgment information. The accuracy of the first event information can be ensured based on the event judgment information.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, device and electronic device for determining legal event determination information. Background Art

[0002] In the legal consultation scenario, users can consult information related to legal cases through the legal consultation system. When the legal consultation system generates a corresponding response based on the consultation information input by the user, it needs to detect the legal events involved in the consultation information. Among them, legal events refer to the legal relationships that legal subjects may be involved in. Therefore, the legal consultation system can further process the consultation information based on the determined legal events (such as retrieving relevant cases and legal basis, etc.) to provide users with accurate consulting opinions. Summary of the invention

[0003] The embodiments of the present application provide a method, device and electronic device for determining legal event determination information, which can determine event determination information based on first event information corresponding to first question information, thereby ensuring the accuracy of the first event information corresponding to the identified first question information based on the event determination information. Specifically, the embodiments of the present application disclose the following technical solutions:

[0004] A first aspect of an embodiment of the present application provides a method for determining legal event determination information, the method comprising: obtaining first event information corresponding to first question information input by a user, and determining multiple preset texts associated with the first event information in a preset database based on the first event information; processing the first preset text to obtain multiple search pairs corresponding to the first preset text; wherein the first preset text is any preset text among the multiple preset texts, and each of the multiple search pairs includes a search identifier and a search content; clustering the multiple search pairs corresponding to the first preset text to obtain multiple candidate seed search pairs; determining a target confidence score for each of the multiple candidate seed search pairs; wherein the target confidence score is related to the correlation between each of the candidate seed search pairs and the first event information, and the number of search pairs in the legal category corresponding to each of the candidate seed search pairs; determining the candidate seed search pairs whose target confidence scores among the multiple candidate seed search pairs are greater than or equal to the preset scores as target seed search pairs; and determining the search content of the target seed search pairs as the event determination information corresponding to the first question information.

[0005] In some embodiments, the above-mentioned multiple search pairs corresponding to the above-mentioned first preset text are clustered to obtain multiple candidate seed search pairs, including: in the clustering process of the current round, multiple first seed search pairs obtained in the clustering process of the previous round and multiple unclustered first search pairs are obtained; wherein the above-mentioned multiple search pairs include the above-mentioned multiple first seed search pairs and the above-mentioned multiple first search pairs, and the sum of the number of the above-mentioned multiple first seed search pairs and the above-mentioned multiple first search pairs is equal to the preset number; the above-mentioned multiple first seed search pairs and the above-mentioned multiple first search pairs are clustered to obtain multiple second search pairs corresponding to each of the above-mentioned legal categories in the multiple legal categories; Among the above-mentioned multiple second search pairs corresponding to each of the above-mentioned legal categories, determine the second seed search pairs corresponding to each of the above-mentioned legal categories, and determine the multiple unclustered second search pairs among the above-mentioned multiple search pairs based on the above-mentioned preset number, the multiple first search pairs and the multiple second seed search pairs; in the next round of clustering process, cluster the multiple second seed search pairs and the multiple second search pairs until there are no unclustered search pairs among the above-mentioned multiple search pairs, and obtain the multiple candidate seed search pairs determined by the last round of clustering process; wherein, each of the above-mentioned multiple candidate seed search pairs corresponds to a different legal category.

[0006] In some embodiments, the second seed retrieval pairs corresponding to each of the above-mentioned legal categories are determined among the above-mentioned multiple second retrieval pairs corresponding to each of the above-mentioned legal categories, including: determining the semantic vector corresponding to each of the above-mentioned second retrieval pairs in each of the above-mentioned legal categories; determining the total distance between each first semantic vector and the second semantic vector in each of the above-mentioned legal categories according to the semantic vector corresponding to each of the above-mentioned second retrieval pairs; wherein the above-mentioned first semantic vector is the semantic vector corresponding to any second retrieval pair among the above-mentioned multiple second retrieval pairs corresponding to each of the above-mentioned legal categories, and the above-mentioned second semantic vector is the semantic vector corresponding to the second retrieval pair other than the second retrieval pair corresponding to the above-mentioned first semantic vector; determining the target semantic vector with the shortest total distance to the above-mentioned second semantic vector among the multiple first semantic vectors, and determining the second retrieval pair corresponding to the above-mentioned target semantic vector as the above-mentioned second seed retrieval pair corresponding to each of the above-mentioned legal categories.

[0007] In some embodiments, the above-mentioned determination of the target confidence score of each of the above-mentioned multiple candidate seed retrieval pairs includes: determining the first confidence score of each of the above-mentioned candidate seed retrieval pairs according to the correlation between each of the above-mentioned candidate seed retrieval pairs and the above-mentioned first event information; wherein, the higher the correlation between each of the above-mentioned candidate seed retrieval pairs and the above-mentioned first event information, the higher the first confidence score of each of the above-mentioned candidate seed retrieval pairs; determining the number of retrieval pairs in the legal category corresponding to each of the above-mentioned candidate seed retrieval pairs, and determining the second confidence score of each of the above-mentioned candidate seed retrieval pairs according to the number of retrieval pairs corresponding to each of the above-mentioned candidate seed retrieval pairs; wherein, the more the number of retrieval pairs corresponding to each of the above-mentioned candidate seed retrieval pairs, the higher the second confidence score of each of the above-mentioned candidate seed retrieval pairs; based on the first confidence score and the second confidence score of each of the above-mentioned candidate seed retrieval pairs, determine the target confidence score of each of the above-mentioned candidate seed retrieval pairs.

[0008] In some embodiments, the above-mentioned determination of the search content of the above-mentioned target seed search pair as the event judgment information corresponding to the above-mentioned first question information includes: if the ratio of the number of the above-mentioned target seed search pairs to the number of the above-mentioned multiple candidate seed search pairs is greater than or equal to a preset ratio, then the search content of the above-mentioned target seed search pair is determined as the above-mentioned event judgment information.

[0009] In some embodiments, the above method also includes: if the ratio of the number of the above-mentioned target seed retrieval pairs to the number of the above-mentioned multiple candidate seed retrieval pairs is less than the above-mentioned preset ratio, and the number of times the clustering is executed in a loop is less than or equal to the preset number of executions, then continue to cluster the above-mentioned multiple retrieval pairs until the ratio of the number of the above-mentioned target seed retrieval pairs to the number of the above-mentioned multiple candidate seed retrieval pairs is greater than or equal to the above-mentioned preset ratio, or the number of times the clustering is executed in the loop is greater than the above-mentioned preset number of executions.

[0010] In some embodiments, the method further includes: if the number of times the clustering is executed in the loop is greater than the preset number of executions, processing the second preset text among the multiple preset texts to obtain multiple retrieval pairs corresponding to the second preset text; wherein the second preset text is any preset text among the multiple preset texts except the first preset text; clustering the multiple retrieval pairs corresponding to the second preset text to determine the target seed retrieval pair corresponding to the second preset text, and determining the retrieval content of the target seed retrieval pair corresponding to the second preset text as the event judgment information corresponding to the first question information.

[0011] In some embodiments, the above-mentioned event determination information is used to determine whether the above-mentioned first event information is established; when it is determined that the above-mentioned first event information is established, the above-mentioned first event information is the target event information corresponding to the above-mentioned first question information; when it is impossible to determine whether the above-mentioned first event information is established, the above-mentioned event determination information is also used to determine the second question information to obtain the user's reply information to the above-mentioned second question information; the above-mentioned reply information is used to determine the second event information corresponding to the above-mentioned first question information, and the above-mentioned second event information is the target event information corresponding to the above-mentioned first question information.

[0012] A second aspect of an embodiment of the present application provides a device for determining legal event determination information, the device comprising: an acquisition module, configured to acquire first event information corresponding to first question information input by a user, and determine multiple preset texts associated with the first event information in a preset database based on the first event information; a processing module, configured to process the first preset text to obtain multiple retrieval pairs corresponding to the first preset text; wherein the first preset text is any preset text among the multiple preset texts, and each of the multiple retrieval pairs includes a retrieval identifier and a retrieval content; a clustering module, configured to cluster the multiple retrieval pairs corresponding to the first preset text processing, and obtaining a plurality of candidate seed retrieval pairs; a first determining module is configured to determine a target confidence score of each of the plurality of candidate seed retrieval pairs; wherein the target confidence score is related to the degree of association between each of the candidate seed retrieval pairs and the first event information, and the number of retrieval pairs in the legal category corresponding to each of the candidate seed retrieval pairs; a second determining module is configured to determine the candidate seed retrieval pairs whose target confidence scores among the plurality of candidate seed retrieval pairs are greater than or equal to a preset score as target seed retrieval pairs; a third determining module is configured to determine the retrieval content of the target seed retrieval pair as the event determination information corresponding to the first question information.

[0013] A third aspect of an embodiment of the present application provides an electronic device, comprising: one or more processors and a memory, the memory being configured to: store one or more programs; wherein, when the one or more programs are executed by one or more processors, the one or more processors implement the method for determining the legal event determination information described in the first aspect above.

[0014] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium, which stores computer program instructions. When a computer reads the instructions, the method for determining legal event determination information described in the first aspect is executed.

[0015] A fifth aspect of an embodiment of the present application provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the method for determining the legal event judgment information described in the first aspect above. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 A flowchart of a method for determining legal event determination information provided in some embodiments of the present application; Figure 2 A flowchart of another method for determining legal event determination information provided in some embodiments of the present application; Figure 3 A flowchart of another method for determining legal event determination information provided in some embodiments of the present application; Figure 4 A flowchart of another method for determining legal event determination information provided in some embodiments of the present application; Figure 5 A flowchart of another method for determining legal event determination information provided in some embodiments of the present application; Figure 6 A schematic diagram of a device for determining legal event determination information provided in some embodiments of the present application; Figure 7 A schematic diagram of an electronic device according to some embodiments of the present application. DETAILED DESCRIPTION

[0018] In order to enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention and to make the above-mentioned purposes, features and advantages of the embodiments of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention are further described in detail below with reference to the accompanying drawings.

[0019] When determining the legal events involved in the consulting information input by the user, since the consulting information input by the user is usually colloquial, there may not be enough information in the consulting information for legal event detection, which may lead to certain deviations in the detection of legal events.

[0020] Based on the above technical problems, the present application provides a method, device and electronic device for determining legal event judgment information, which can identify the legal events involved in the consulting information input by the user, and further determine the event judgment information based on the identified legal event information, so that it can subsequently determine whether the above legal event information is accurate based on the event judgment information and the consulting information.

[0021] It should be noted that the training samples used in the training process of the neural network model involved in this application are all from authorized legal documents, judgments, case descriptions, etc., and the conclusions obtained by the method for determining the legal event judgment information provided in this application are only used to form consulting opinions for users for reference.

[0022] The following is a detailed description of the method for determining the legal event determination information provided by this application.

[0023] Figure 1 A flowchart of a method for determining legal event determination information provided in some embodiments of the present application, such as Figure 1 As shown, the method for determining the legal event determination information may include steps 110 to 140.

[0024] Step 110: Acquire first event information corresponding to first question information input by the user, and determine a plurality of preset texts associated with the first event information in a preset database based on the first event information.

[0025] In some embodiments, a user may input legal consulting information (hereinafter referred to as first question information) in a user interface provided by a legal consulting system (hereinafter referred to as a central control system). The central control system may call a corresponding legal tool in response to the first question information input by the user to process the first question information to obtain a processing result, thereby summarizing the processing results obtained by each legal tool, obtaining a final consulting opinion, and outputting it to the user.

[0026] Among them, the legal tool may include a legal event detection model and a legal event establishment condition determination model (hereinafter referred to as the establishment condition determination model). The legal event detection model can preliminarily identify the legal events involved in the first question information input by the user to obtain the legal event detection result (i.e., the first event information). Exemplarily, the legal event detection model can extract the contextual relationship corresponding to each entity in the first question information input by the user (i.e., the initial features corresponding to each entity), and update the initial features corresponding to each entity by hierarchical propagation and aggregation of neighbor node information, so as to finally obtain the core information corresponding to each entity and the core relationship between each entity; then, based on the core information corresponding to each entity and the core relationship between each entity, determine the legal event information corresponding to the first question information (i.e., the first event information).

[0027] Since the content of the first question information input by the user is usually colloquial, it may not provide comprehensive information for legal event detection. Therefore, it is not possible to determine whether the first event information is consistent with the legal event actually consulted by the user. Therefore, the establishment condition determination model can determine the event determination information corresponding to the first event information, and thus determine whether the first question information is accurate through the event determination information.

[0028] In some embodiments, after the establishment condition determination model obtains the first event information output by the legal event detection model, it can retrieve the judgment document (i.e., preset text) related to the first event information in the preset data. For example, if the first question information input by the user is "I rented A's shop and signed a three-year lease contract, but now I am losing money due to an unexpected business, can I ask to terminate the lease contract early?", and after the legal event detection model processes the first question information, the first event information obtained is "Contract termination under contract deadlock", then the establishment condition determination model can retrieve the judgment document related to "Contract termination under contract deadlock" in the preset database.

[0029] Step 120: Process the first preset text to obtain a plurality of search pairs corresponding to the first preset text.

[0030] In some embodiments, the establishment condition determination model may then analyze any preset text (ie, the first preset text) among the plurality of preset texts through a large language model (LLM) to obtain a plurality of search pairs corresponding to the first preset text.

[0031] Each of the multiple search pairs includes a search identifier and a search content. The search identifier is used to represent a legal act or a legal event, such as "theft", "contract termination", "tort", etc. The search content is used to represent an entity associated with the legal act or legal event, such as "Zhang San", "5,000 yuan", "malicious breach of contract", etc. In the preset text, each legal act may correspond to one or more entities, and multiple different search pairs can be determined based on each legal act and each entity.

[0032] Step 130 , clustering the multiple search pairs corresponding to the first preset text to obtain multiple candidate seed search pairs.

[0033] In some embodiments, after determining the multiple search pairs corresponding to the first preset text, the condition determination model can cluster the multiple search pairs through the large language model LLM to determine multiple candidate seed search pairs. Exemplarily, in order to avoid excessive burden on the model caused by clustering multiple search pairs at one time, multiple rounds of clustering can be used to cluster the multiple search pairs, and multiple rounds of clustering can also enable the next round of clustering process to learn the clustering results of the previous round, thereby improving the clustering effect.

[0034] Exemplarily, in each round of clustering, a preset number of search pairs (including seed search pairs obtained from the previous round of clustering and unclustered search pairs) can be selected and clustered to obtain multiple search pairs corresponding to each legal category in one or more legal categories, and then seed search pairs are determined from the multiple search pairs corresponding to each legal category. The seed search pairs are representative search pairs among the multiple search pairs corresponding to each legal category. After completing the clustering of all search pairs, the final multiple candidate seed search pairs can be obtained. Each candidate seed search pair corresponds to a legal category.

[0035] Among them, the legal category can be determined according to the legal field to which the legal case belongs or the specific type of the legal case, etc. For example, the legal category may include criminal law (such as intentional injury, theft), civil law (such as contract disputes, property inheritance), administrative law (such as administrative penalties), intellectual property law (such as patents, trademarks, copyrights), labor law (such as labor contracts, work-related injury compensation), etc.; or include contracts (such as lease contract disputes, sales contract disputes, service contract disputes), torts (such as personal injury compensation, traffic accident liability), labor disputes (such as labor contract termination, unpaid overtime wages), etc. It should be noted that the specific content of the above legal categories is only an example, and this is not limited in this embodiment.

[0036] Step 140: determine a target seed search pair that meets a preset condition among a plurality of candidate seed search pairs, and determine the search content of the target seed search pair as event determination information corresponding to the first question information.

[0037] In some embodiments, after determining the above-mentioned multiple candidate seed retrieval pairs, a target seed retrieval pair that meets the preset conditions can be determined from the above-mentioned multiple candidate seed retrieval pairs. Among them, the target seed retrieval pair can be a candidate retrieval pair with a high semantic association with the first event information, and the number of the target seed retrieval pairs can be one or more. Then, the event determination information corresponding to the first question information is determined based on the retrieval identifier and retrieval content of the above-mentioned target seed retrieval pair.

[0038] For example, if the first question information input by the user is "Can I terminate the shop lease contract?", the first event information obtained after legal event detection on the first question information is the termination of the contract under a contract deadlock, and the search identifier of the determined target seed search pair is "contract termination", and the search content is "it is obviously unfair for the defaulting party to continue to perform the contract", then the search content of the target seed search pair can be determined as the event judgment information corresponding to the first question information.

[0039] Through the above scheme, after the legal events involved in the consulting information input by the user are identified through the legal event detection model and the first event information is obtained, the corresponding event judgment information can be further determined based on the first event information, so that the accuracy of the above first event information can be determined based on the event judgment information and the consulting information.

[0040] Figure 2 A flowchart of another method for determining legal event determination information provided in some embodiments of the present application, such as Figure 2 As shown, the above step 130 may include steps 210 to 240.

[0041] Step 210: In the current round of clustering process, a plurality of first seed retrieval pairs obtained in the previous round of clustering process and a plurality of unclustered first retrieval pairs are obtained.

[0042] In some embodiments, during multiple rounds of clustering of multiple retrieval pairs corresponding to the first preset text, the current round of clustering process first obtains multiple seed retrieval pairs (i.e., first seed retrieval pairs) obtained by the previous round of clustering process and multiple retrieval pairs that have not been clustered (i.e., first retrieval pairs).

[0043] For example, the number of search pairs is 1000 and the preset number is 100. In the first round of clustering, 100 search pairs are selected from the 1000 search pairs for unsupervised clustering to obtain multiple search pairs corresponding to each of the multiple legal categories, and the first seed search pairs corresponding to each legal category are determined from the multiple search pairs corresponding to each legal category. If the number of first seed search pairs is 30, then in the second round of clustering, 70 unclustered first search pairs are selected from the remaining 900 search pairs (that is, the sum of the number of first seed search pairs and first search pairs is equal to the preset number of 100), and the above 50 first seed search pairs and 70 first search pairs are clustered again.

[0044] Step 220 , clustering the plurality of first seed search pairs and the plurality of first search pairs to obtain a plurality of second search pairs corresponding to each of the plurality of legal categories.

[0045] In some embodiments, after the above-mentioned multiple first seed search pairs and multiple first search pairs are obtained through the previous round of clustering process, the multiple first seed search pairs and multiple first search pairs are subjected to unsupervised clustering through the current round of clustering process to obtain multiple second search pairs corresponding to each of the multiple legal categories. Using the above example, after clustering the above-mentioned 50 first seed search pairs and 70 first search pairs, multiple second search pairs corresponding to each legal category can be obtained, such as multiple second search pairs corresponding to 20 legal categories.

[0046] In some examples, an upper limit value for the number of legal categories obtained in each round of clustering process may be set, such as setting the number of legal categories obtained when clustering 100 search pairs in each round to be at most 60.

[0047] In some examples, different weights may be set for the search identifier and the search content during the clustering process. For example, the weight corresponding to the search identifier may be set to be smaller than the weight corresponding to the search content (e.g., the weight corresponding to the search identifier is set to 0.4, and the weight corresponding to the search content is set to 0.6), so that the basis for the establishment condition determination model when clustering multiple search pairs will be more biased towards the search content of each search pair.

[0048] Step 230, determining a second seed search pair corresponding to each legal category among the multiple second search pairs corresponding to each legal category, and determining a plurality of unclustered second search pairs among the multiple search pairs according to a preset number, the plurality of first search pairs and the plurality of second seed search pairs.

[0049] In some embodiments, after obtaining a plurality of second search pairs corresponding to each legal category through the clustering process of the current round, a representative second seed search pair is determined from the plurality of second search pairs corresponding to each legal category.

[0050] Exemplarily, the method for determining the second seed search pairs corresponding to each legal category can be determined based on the distance between each second search pair (such as Euclidean distance), or can be obtained by semantically summarizing multiple second search pairs corresponding to each legal category through a large language model, which is not limited in this embodiment.

[0051] In some embodiments, after the current round of clustering is completed, multiple unclustered second search pairs are obtained from the multiple search pairs according to a preset number, and the sum of the number of the multiple second search pairs and the number of the multiple second seed search pairs is equal to the preset number. Using the above example, if multiple second search pairs corresponding to 20 legal categories are obtained, the number of multiple second seed search pairs determined is 20 (i.e., each legal category corresponds to a second seed search pair), and then 80 unclustered second search pairs are selected from the remaining 800 search pairs (i.e., the sum of the number of second seed search pairs and the number of second search pairs is equal to the preset number of 100), and the next round of clustering is performed on the above 20 second seed search pairs and 80 second search pairs.

[0052] Step 240: cluster the multiple second seed retrieval pairs and the multiple second retrieval pairs in the next round of clustering process until there are no unclustered retrieval pairs in the multiple retrieval pairs, and obtain multiple candidate seed retrieval pairs determined by the last round of clustering process.

[0053] In some embodiments, the plurality of second seed search pairs and the plurality of second search pairs are clustered in the next round of clustering, and so on, until all the plurality of search pairs are clustered (i.e., there are no unclustered search pairs in the plurality of search pairs), and a plurality of candidate seed search pairs determined by the last round of clustering are obtained. Each of the plurality of candidate seed search pairs corresponds to a different legal category.

[0054] Through the above scheme, multiple search pairs corresponding to the first preset text can be clustered through multiple rounds of clustering, thereby improving the clustering effect, that is, obtaining more accurate classification results, and then determining more accurate event judgment information based on the seed search pairs.

[0055] Figure 3 A flowchart of another method for determining legal event determination information provided in some embodiments of the present application, such as Figure 3 As shown, the above step 230 of “determining a second seed search pair corresponding to each legal category among a plurality of second search pairs corresponding to each legal category” may include steps 310 to 330 .

[0056] Step 310: Determine the semantic vector corresponding to each second search pair in each legal category.

[0057] In some embodiments, when determining the second seed search pairs corresponding to each legal category based on the distance (such as the Euclidean distance) between each second search pair, the semantic vector corresponding to each second search pair in each legal category may be determined first. For example, the semantic vector corresponding to the search content of each second search pair may be determined.

[0058] For example, in the legal category of "contract termination", the search content of the second search pair and the semantic vectors corresponding to each search content are: S1 = "Although the defaulting party breached the contract first, it was not in bad faith", V1 = [0.8, 0.5]; S2 = "It is obviously unfair for the defaulting party to continue to perform the contract", V2 = [0.7, 0.6]; S3 = "The observant party refuses to terminate the contract, which violates the principle of good faith", V3 = [0.9, 0.4]. It should be noted that the specific values ​​of the semantic vectors corresponding to the above search contents are only examples.

[0059] Step 320: Determine the total distance between each first semantic vector and the second semantic vector in each legal category according to the semantic vector corresponding to each second search pair.

[0060] In some embodiments, after determining the semantic vectors corresponding to each second search pair in each legal category, the distance (such as Euclidean distance) between the semantic vectors of each second search pair in each legal category and the semantic vectors of other second search pairs in the legal category is determined, that is, the distance between each first semantic vector and the second semantic vector in each legal category is determined, and the distance between each first semantic vector and the second semantic vector is added to obtain the total distance between each first semantic vector and the second semantic vector. The first semantic vector is a semantic vector corresponding to any second search pair among the multiple second search pairs corresponding to each legal category, and the second semantic vector is a semantic vector corresponding to a second search pair other than the second search pair corresponding to the first semantic vector.

[0061] Using the above example, in the second search pair S1, S2 and S3, the Euclidean distance between the semantic vector V1 of the second search pair S1 and the semantic vector V2 of S2 is ; The second search pair is the Euclidean distance between the semantic vector V1 of S1 and the semantic vector V3 of S3 Then the total distance between the semantic vector V1 of the second search pair S1 and the semantic vectors of the second search pair S2 and S3 is .

[0062] Similarly, the total distance between the semantic vector V2 of the second search pair S2 and the semantic vector V1 of the second search pair S1 and the semantic vector V3 of the second search pair S3 can be determined. ; and the total distance between the semantic vector V3 of the second search pair S3 and the semantic vector V1 of the second search pair S1 and the semantic vector V2 of the second search pair S2 .

[0063] Step 330 , determining a target semantic vector having the shortest total distance to the second semantic vector among the multiple first semantic vectors, and determining the second search pair corresponding to the target semantic vector as the second seed search pair corresponding to each legal category.

[0064] In some embodiments, after obtaining the total distances corresponding to the above-mentioned first semantic vectors, the first semantic vector with the shortest total distance can be determined as the target semantic vector, and the second search pair corresponding to the target semantic vector is the second seed search pair corresponding to the legal category to which it belongs.

[0065] Using the above example, the total distance corresponding to the semantic vector V1 of the second search pair S1 is , the total distance corresponding to the semantic vector V2 of the second search pair S2 And the total distance corresponding to the semantic vector V3 of the second search pair S3 In, total distance The value of is the smallest, so the semantic vector V1 of the second search pair S1 can be determined as the target semantic vector, and the second search pair S1 is the second seed search pair in the legal category of "contract termination".

[0066] Through the above scheme, when determining the seed retrieval pair, by determining the sum of the distances between the semantic vectors of each retrieval pair in each legal category and the semantic vectors of all other retrieval pairs, and selecting the retrieval pair with the smallest sum of distances as the seed retrieval pair, the representativeness and centrality of the seed retrieval pair can be ensured, thereby ensuring the accuracy of the event judgment information determined based on the seed retrieval pair.

[0067] Figure 4 A flowchart of another method for determining legal event determination information provided in some embodiments of the present application, such as Figure 4 As shown, the “determining a target seed retrieval pair satisfying a preset condition from a plurality of candidate seed retrieval pairs” in the above step 140 may include steps 410 to 420 .

[0068] Step 410, determining a target confidence score for each candidate seed retrieval pair among a plurality of candidate seed retrieval pairs.

[0069] In some embodiments, after finally obtaining the candidate seed retrieval pairs corresponding to each legal category through multiple rounds of clustering, the target confidence score of each candidate seed retrieval pair can be determined according to a preset scoring rule.

[0070] Among them, the target confidence score may be related to the degree of association between each candidate seed retrieval pair and the first event information, and the number of retrieval pairs in the legal category corresponding to each candidate seed retrieval pair. For example, the higher the degree of association between each candidate seed retrieval pair and the first event information, and the more retrieval pairs in the legal category corresponding to each candidate seed retrieval pair, the higher the target confidence score of each candidate seed retrieval pair; conversely, the lower the degree of association between each candidate seed retrieval pair and the first event information, and the fewer retrieval pairs in the legal category corresponding to each candidate seed retrieval pair, the lower the target confidence score of each candidate seed retrieval pair.

[0071] Step 420: Determine the candidate seed retrieval pairs whose target confidence scores are greater than or equal to a preset score among the multiple candidate seed retrieval pairs as target seed retrieval pairs.

[0072] In some embodiments, then, candidate seed retrieval pairs whose target confidence scores are greater than or equal to the preset scores can be determined from multiple candidate seed retrieval pairs, and these candidate seed retrieval pairs are determined as target seed retrieval pairs. For example, if the target confidence score corresponding to candidate seed retrieval pair S1 is 80, the target confidence score corresponding to candidate seed retrieval pair S2 is 60, the target confidence score corresponding to candidate seed retrieval pair S3 is 50, the target confidence score corresponding to candidate seed retrieval pair S4 is 30, the target confidence score corresponding to candidate seed retrieval pair S5 is 70, and the preset score is 60, then the candidate seed retrieval pair S1, candidate seed retrieval pair S2, and candidate seed retrieval pair S5 whose target confidence scores are greater than or equal to 60 are target seed retrieval pairs.

[0073] Through the above scheme, the confidence score of each candidate seed retrieval pair is determined based on the correlation between each candidate seed retrieval pair and the first event information and the number of retrieval pairs in the legal category corresponding to each candidate seed retrieval pair, so that the target seed retrieval pair determined based on the confidence score of each candidate seed retrieval pair can be more relevant to the first event information and can more accurately represent each legal category, thereby further improving the accuracy of subsequent determination of whether the first event information is true based on the target seed retrieval pair.

[0074] Figure 5 A flowchart of another method for determining legal event determination information provided in some embodiments of the present application, such as Figure 5 As shown, the above step 410 may include steps 510 to 530.

[0075] Step 510: Determine a first confidence score for each candidate seed retrieval pair according to the degree of association between each candidate seed retrieval pair and the first event information.

[0076] In some embodiments, when determining the target confidence score of each candidate seed retrieval pair, the first confidence score of each candidate seed retrieval pair may be determined according to the correlation between each candidate seed retrieval pair and the first event information. The higher the correlation between each candidate seed retrieval pair and the first event information, the higher the first confidence score of each candidate seed retrieval pair.

[0077] Step 520: determine the number of search pairs in the legal category corresponding to each candidate seed search pair, and determine a second confidence score for each candidate seed search pair according to the number of search pairs corresponding to each candidate seed search pair.

[0078] In some embodiments, the second confidence score of each candidate seed search pair can be determined according to the number of search pairs in the legal category corresponding to each candidate seed search pair. The more search pairs each candidate seed search pair corresponds to, the higher the second confidence score of each candidate seed search pair.

[0079] Step 530: Determine a target confidence score for each candidate seed retrieval pair based on the first confidence score and the second confidence score for each candidate seed retrieval pair.

[0080] In some embodiments, after determining the first confidence score and the second confidence score corresponding to each candidate seed retrieval pair, the target confidence score corresponding to each candidate seed retrieval pair can be determined according to the sum of the first confidence score and the second confidence score. For example, if the first confidence score score1 corresponding to the candidate seed retrieval pair S1 is 80 and the second confidence score score2 is 60, then the target confidence score corresponding to the candidate seed retrieval pair S1 is score=score1+score2=80+60=140.

[0081] Exemplarily, different weights may be set for the first confidence score and the second confidence score, respectively, and the target confidence score may be determined based on the first confidence score, the second confidence score, and the corresponding weights. Using the above example, if the weight of the first confidence score is set to 0.6 and the weight of the second confidence score is set to 0.4, then the target confidence score corresponding to the candidate seed retrieval pair S1 is score=0.6×score1+0.4×score2=0.6×80+0.4×60=72.

[0082] Through the above scheme, the confidence score of each candidate seed retrieval pair is determined based on the correlation between each candidate seed retrieval pair and the first event information, which can improve the accuracy in determining the target seed retrieval pair; the confidence score of each candidate seed retrieval pair is determined based on the number of retrieval pairs corresponding to each candidate seed retrieval pair, which can improve the universality in determining the target seed retrieval pair and improve the generalization ability to reduce the overfitting problem.

[0083] In some embodiments, the above step 140 includes: if the ratio of the number of target seed search pairs to the number of multiple candidate seed search pairs is greater than or equal to a preset ratio, determining the search content of the target seed search pair as event determination information.

[0084] In some embodiments, after obtaining multiple candidate seed retrieval pairs and determining the target confidence score of each candidate seed retrieval pair, it can be further determined whether the number of target seed retrieval pairs reaches a certain proportion in all candidate seed retrieval pairs. Exemplarily, the ratio of the number of target seed retrieval pairs to the number of all candidate seed retrieval pairs can be determined, and it can be determined whether the ratio is greater than or equal to a preset ratio. If the proportion of the target seed retrieval pair in all candidate seed retrieval pairs is greater than the preset ratio, the retrieval content of the target seed retrieval pair is determined as the event determination information corresponding to the first question information.

[0085] For example, if the total number of candidate seed search pairs is 5, the number of target seed search pairs is 3, and the preset ratio is 0.6, then the proportion of target seed search pairs in candidate seed search pairs is 3 / 5=0.6, that is, the proportion of target seed search pairs is equal to the preset ratio, so the search content of the target seed search pair can be determined as the event determination information corresponding to the first question information. If the search content of the target seed search pair S1 is "although the defaulting party breached the contract first, it was not a malicious breach of contract", the search content of the target seed search pair S2 is "the defaulting party continues to perform the contract, which is obviously unfair to it", and the search content of the target seed search pair S3 is "the abiding party refuses to terminate the contract, which violates the principle of good faith", then the event determination information corresponding to the first question information is the above search content.

[0086] In some embodiments, the above method also includes: if the ratio of the number of target seed retrieval pairs to the number of multiple candidate seed retrieval pairs is less than a preset ratio, and the number of times the clustering is executed in a loop is less than or equal to the preset number of executions, then continue to cluster the multiple retrieval pairs until the ratio of the number of target seed retrieval pairs to the number of multiple candidate seed retrieval pairs is greater than or equal to the preset ratio, or the number of times the clustering is executed in a loop is greater than the preset number of executions.

[0087] In some embodiments, if the ratio of the number of target seed retrieval pairs to the number of multiple candidate seed retrieval pairs is less than a preset ratio, and the number of times multiple rounds of clustering are re-executed (i.e., the number of times clustering is cyclically executed) is less than or equal to the preset number of executions, then multiple rounds of clustering can be re-performed on the multiple retrieval pairs corresponding to the first preset text until the ratio of the number of target seed retrieval pairs to the number of multiple candidate seed retrieval pairs obtained is greater than or equal to the preset ratio, or the number of times multiple rounds of clustering are re-executed is greater than the preset number of executions.

[0088] For example, if the total number of candidate seed retrieval pairs corresponding to the first preset text is 10, the number of target seed retrieval pairs is 2, and the preset ratio is 0.6, and the preset number of executions is 5 times, then the proportion of target seed retrieval pairs in the candidate seed retrieval pairs is 2 / 10=0.2, that is, the proportion of target seed retrieval pairs is less than the preset ratio. Then, when the number of re-executions of multiple rounds of clustering is less than or equal to 5 times, the multiple retrieval pairs corresponding to the first preset text can be re-clustered for multiple rounds until the proportion of target seed retrieval pairs corresponding to the first preset text in the candidate seed retrieval pairs is greater than the preset ratio of 0.6, or the number of re-executions of multiple rounds of clustering is greater than 5 times.

[0089] In some embodiments, the above method also includes: if the number of times the clustering is executed in a loop is greater than the preset number of executions, processing the second preset text among the multiple preset texts to obtain multiple retrieval pairs corresponding to the second preset text; clustering the multiple retrieval pairs corresponding to the second preset text to determine the target seed retrieval pair corresponding to the second preset text, and determining the retrieval content of the target seed retrieval pair corresponding to the second preset text as the event judgment information corresponding to the first question information.

[0090] In some embodiments, if after multiple re-clustering (such as the number of cyclic clustering executions is greater than a preset number of executions), the ratio of the number of target seed retrieval pairs to the number of multiple candidate seed retrieval pairs is still less than a preset ratio, then any preset text other than the first preset text (i.e., the second preset text) can be reselected from the multiple preset texts.

[0091] Similarly, the condition determination model processes the second preset text to obtain multiple search pairs corresponding to the second preset text; and performs multiple rounds of clustering on the multiple search pairs corresponding to the second preset text to determine multiple candidate seed search pairs and target seed search pairs corresponding to the second preset text. If the ratio of the number of target seed search pairs corresponding to the second preset text to the number of multiple candidate seed search pairs corresponding to the second preset text is greater than or equal to the preset ratio, the search content of the target seed search pair is determined as event determination information; if the ratio of the number of target seed search pairs corresponding to the second preset text to the number of multiple candidate seed search pairs is less than the preset ratio, and the number of clustering cycles is less than or equal to the preset number of executions, the multiple search pairs continue to be clustered. And so on, until the ratio of the number of target seed search pairs corresponding to the second preset text to the number of multiple candidate seed search pairs is greater than or equal to the preset ratio, or the number of re-executions of multiple rounds of clustering is greater than the preset number of executions.

[0092] If it is impossible to obtain a target seed retrieval pair from the second preset text that can serve as the event judgment information corresponding to the first question information, continue to obtain any preset text (i.e., the third preset text) other than the first preset text and the second preset text from the multiple preset texts, and process the third preset text...and so on, until the target seed retrieval pair corresponding to any preset text among the multiple preset texts can serve as the event judgment information corresponding to the first question information, or all the preset texts cannot provide event judgment information corresponding to the first question information.

[0093] In some embodiments, the above method also includes: event determination information is used to determine whether the first event information is established; when it is determined that the first event information is established, the first event information is the target event information corresponding to the first question information; when it is impossible to determine whether the first event information is established, the event determination information is also used to determine the second question information to obtain the user's reply information to the second question information; the reply information is used to determine the second event information corresponding to the first question information, and the second event information is the target event information corresponding to the first question information.

[0094] In some embodiments, after determining the event determination information corresponding to the first question information based on the preset text, it is possible to determine whether the first event information determined by the legal event detection model is accurate based on the event determination information. In the case where the first question information does not lack necessary information, it is possible to determine whether the first event information is established based on the first question information and the event determination information, wherein the necessary information refers to information used to accurately identify the legal event. If the first event information is established, the first event information is determined as the target event information corresponding to the first question information.

[0095] In the case where necessary information is missing in the first question information, it is impossible to determine whether the first event information is established based on the first question information and the event determination information. At this time, the central control system can determine and output the second question information (or called information slot) based on the event determination information, and obtain the reply information input by the user for the second question information; thus, the legal event detection model can supplement and improve the first question information based on the reply information, and perform legal event detection on the supplemented first question information again, and obtain the second event information. The second event information determined by the legal event detection model may be the same as the first event information, or it may be different from the first event information. If the second event information is the same as the first event information, the second event information or the first event information can be determined as the target event information; if the second event information is different from the first event information, the newly detected second event information is determined as the target event information.

[0096] In some embodiments, after determining the final target event information, the central control system can call other legal tools to perform legal case retrieval or legal text retrieval based on the target event information to provide consulting opinions to users.

[0097] Take the first question information input by the user in the user interface of the central control system as "I signed a house rental contract, but the landlord did not deliver the house on the agreed time. I have notified the landlord to terminate the contract, but I have lost 2,000 yuan. Can I ask the landlord to compensate for the loss?" as an example. If the first event information corresponding to the first question information is "contract termination and compensation", and the event determination information corresponding to the first question information is: "the tenant and the landlord signed a house rental contract", "the landlord did not deliver the house on time", "the tenant has notified the landlord to terminate the contract", "the tenant has economic losses", then according to the first question information and the above event determination information, it can be determined that the first question information does not lack necessary information, that is, the content corresponding to the above event determination information can be found in the first question information; and the content in the first question information meets all the event determination information, so it can be determined that the above first event information is established, that is, the first event information is accurate. Therefore, the central control system can call other legal tools to search and integrate legal cases or legal provisions related to "contract termination and compensation", obtain the final legal advice and output it to the user.

[0098] Take the first question information input by the user in the user interface of the central control system as "I signed a three-year shop lease contract with Party A to rent the other party's shop, but since I can't make money now, can I request to terminate the lease contract early?" For example, in the first question information, since the reason for the operating loss is unclear, the basis for the party's request for contract termination may be a contract deadlock or a change of circumstances. Therefore, after the first event information corresponding to the first question information is determined by the legal event detection model (such as determining that the first event information is "contract termination under contract deadlock"), the event determination information corresponding to "contract termination under contract deadlock" can be determined through the establishment condition determination model, so as to determine the necessary information missing in the first question information through the event determination information.

[0099] If the event judgment information corresponding to "contract termination under contract deadlock" determined by the establishment condition judgment model is: 1) Although the defaulting party breached the contract first, it was not a malicious breach; 2) If the defaulting party continues to perform the contract, it will be unfair to the defaulting party; 3) The party that abides by the contract refuses to terminate the contract, which violates the principle of good faith; and according to the above first question information, it can be determined that the user is the defaulting party, but it is impossible to determine the reason for the user's operating loss, so it is impossible to determine whether the user is a malicious breach of contract, and it is also impossible to determine whether continuing to perform the contract is unfair to the user. Therefore, the central control system can generate the corresponding second question information based on the above 1) and 2) event judgment information and output it to the user, such as the second question information can be "What is the reason for your operating loss?", "Have you fully negotiated with the other party?", etc.

[0100] If the user inputs the reply information for the second question information as: "Because my capital chain is broken, I can't continue to operate. After negotiation with the other party, he insisted that I pay three years of rent", then the legal event detection model can supplement the first question information based on the reply information to obtain the target question information, such as "I signed a three-year shop lease contract with A to rent the other party's shop, but because my capital chain is broken, I can't continue to operate. After negotiation with the other party, he insisted that I pay three years of rent. Can I ask to terminate the lease contract in advance?" Then, the legal event detection model can determine that the second event information corresponding to the target question information is "contract termination under contract deadlock". Since the second event information is the same as the first event information, it can be determined that the target event information is "contract termination under contract deadlock". Finally, the central control system can call other legal tools to search and integrate legal cases or legal provisions related to "contract termination under contract deadlock" to obtain the final consulting opinion and output it to the user.

[0101] By applying the technical solution of the present application, event determination information related to the first event information corresponding to the first question information input by the user can be determined in the preset text through multiple rounds of clustering, determining confidence scores, etc., thereby improving the accuracy in determining the event determination information, so as to further accurately determine whether the first event information is established based on the event determination information; and in the case where necessary information is missing in the first question information and it is impossible to determine whether the first event information is established, an information slot can be generated based on the event determination information to guide the user to supplement the necessary information in the first question information, so that the corresponding legal event can be determined based on the complete question information, and then more accurate legal advice can be provided to the user based on the legal event.

[0102] Figure 6 A schematic diagram of a device for determining legal event determination information provided in some embodiments of the present application. Figure 6As shown, the apparatus 600 for determining legal event determination information includes an acquisition module 610 , a processing module 620 , a clustering module 630 , a first determination module 640 , a second determination module 650 and a third determination module 660 .

[0103] The acquisition module 610 is configured to acquire first event information corresponding to the first question information input by the user, and determine a plurality of preset texts associated with the first event information in a preset database based on the first event information.

[0104] The processing module 620 is configured to process a first preset text among the multiple preset texts to obtain multiple search pairs corresponding to the first preset text.

[0105] Each of the multiple search pairs includes a search identifier and a search content.

[0106] The clustering module 630 is configured to perform clustering processing on the multiple search pairs corresponding to the first preset text to obtain multiple candidate seed search pairs.

[0107] The first determination module 640 is configured to determine a target confidence score for each candidate seed retrieval pair among the plurality of candidate seed retrieval pairs.

[0108] The target confidence score is related to the correlation between each candidate seed search pair and the first event information, and the number of search pairs in the legal category corresponding to each candidate seed search pair.

[0109] The second determination module 650 is configured to determine a candidate seed retrieval pair whose target confidence score is greater than or equal to a preset score among the plurality of candidate seed retrieval pairs as a target seed retrieval pair.

[0110] The third determination module 660 is configured to determine the search content of the target seed search pair as the event determination information corresponding to the first question information.

[0111] In some embodiments, the clustering module 630 is specifically configured as follows: in the current round of clustering, a plurality of first seed retrieval pairs and a plurality of unclustered first retrieval pairs obtained in the previous round of clustering are obtained; wherein the plurality of retrieval pairs include a plurality of first seed retrieval pairs and a plurality of first retrieval pairs, and the sum of the number of the plurality of first seed retrieval pairs and the plurality of first retrieval pairs is equal to a preset number; the plurality of first seed retrieval pairs and the plurality of first retrieval pairs are clustered to obtain a plurality of second retrieval pairs corresponding to each of the plurality of legal categories; among the plurality of second retrieval pairs corresponding to each of the plurality of legal categories, a second seed retrieval pair corresponding to each of the plurality of legal categories is determined, and a plurality of unclustered second retrieval pairs are determined in the plurality of retrieval pairs according to the preset number, the plurality of first retrieval pairs and the plurality of second seed retrieval pairs; in the next round of clustering, the plurality of second seed retrieval pairs and the plurality of second retrieval pairs are clustered until there are no unclustered retrieval pairs in the plurality of retrieval pairs, and a plurality of candidate seed retrieval pairs determined by the last round of clustering are obtained; wherein each of the plurality of candidate seed retrieval pairs corresponds to a different legal category.

[0112] In some embodiments, the clustering module 630 is specifically configured to: determine the semantic vector corresponding to each second retrieval pair in each legal category; determine the total distance between each first semantic vector and the second semantic vector in each legal category based on the semantic vector corresponding to each second retrieval pair; wherein the first semantic vector is the semantic vector corresponding to any second retrieval pair among the multiple second retrieval pairs corresponding to each legal category, and the second semantic vector is the semantic vector corresponding to the second retrieval pair other than the second retrieval pair corresponding to the first semantic vector; determine the target semantic vector with the shortest total distance to the second semantic vector among the multiple first semantic vectors, and determine the second retrieval pair corresponding to the target semantic vector as the second seed retrieval pair corresponding to each legal category.

[0113] In some embodiments, the first determination module 640 is specifically configured to: determine the first confidence score of each candidate seed retrieval pair based on the correlation between each candidate seed retrieval pair and the first event information; wherein, the higher the correlation between each candidate seed retrieval pair and the first event information, the higher the first confidence score of each candidate seed retrieval pair; determine the number of retrieval pairs in the legal category corresponding to each candidate seed retrieval pair, and determine the second confidence score of each candidate seed retrieval pair based on the number of retrieval pairs corresponding to each candidate seed retrieval pair; wherein, the more the number of retrieval pairs corresponding to each candidate seed retrieval pair, the higher the second confidence score of each candidate seed retrieval pair; determine the target confidence score of each candidate seed retrieval pair based on the first confidence score and the second confidence score of each candidate seed retrieval pair.

[0114] In some embodiments, the third determination module 660 is specifically configured to: if the ratio of the number of target seed retrieval pairs to the number of multiple candidate seed retrieval pairs is greater than or equal to a preset ratio, determine the retrieval content of the target seed retrieval pair as event determination information.

[0115] In some embodiments, the clustering module 630 is also configured to: if the ratio of the number of target seed retrieval pairs to the number of multiple candidate seed retrieval pairs is less than a preset ratio, and the number of times the clustering is executed in a loop is less than or equal to the preset number of executions, then continue to cluster the multiple retrieval pairs until the ratio of the number of target seed retrieval pairs to the number of multiple candidate seed retrieval pairs is greater than or equal to the preset ratio, or the number of times the clustering is executed in a loop is greater than the preset number of executions.

[0116] In some embodiments, the processing module 620 is also configured to: if the number of times the clustering is executed in a loop is greater than the preset number of executions, then process the second preset text among the multiple preset texts to obtain multiple retrieval pairs corresponding to the second preset text; wherein the second preset text is any preset text among the multiple preset texts except the first preset text; the clustering module 630 is also configured to: perform clustering processing on the multiple retrieval pairs corresponding to the second preset text to determine the target seed retrieval pair corresponding to the second preset text, and determine the retrieval content of the target seed retrieval pair corresponding to the second preset text as the event judgment information corresponding to the first question information.

[0117] In some embodiments, event determination information is used to determine whether first event information is established; when it is determined that the first event information is established, the first event information is the target event information corresponding to the first question information; when it is impossible to determine whether the first event information is established, the event determination information is also used to determine the second question information to obtain the user's reply information to the second question information; the reply information is used to determine the second event information corresponding to the first question information, and the second event information is the target event information corresponding to the first question information.

[0118] Figure 7 A schematic diagram of an electronic device provided for some embodiments of the present application. In some embodiments, the electronic device includes one or more processors and a memory. The memory is configured to store one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method for determining the legal event determination information in the above-mentioned embodiment.

[0119] like Figure 7 As shown, the electronic device 700 includes: a processor (processor) 701 and a memory 702. Exemplarily, the electronic device 700 may also include: a communication interface (Communications Interface) 703 and a communication bus 704.

[0120] The processor 701, the memory 702 and the communication interface 703 communicate with each other via a communication bus 704. The communication interface 703 is used to communicate with other devices such as a client or a network element of another server.

[0121] In some embodiments, the processor 701 is used to execute the program 705, and specifically can execute the relevant steps in the above-mentioned method for determining the legal event determination information. Specifically, the program 705 may include program code, and the program code includes computer executable instructions.

[0122] Exemplarily, the processor 701 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement some embodiments of the present application. The electronic device 700 may include one or more processors, which may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0123] In some embodiments, the memory 702 is used to store the program 705. The memory 702 may include a high-speed RAM memory, and may also include a non-volatile memory (NVM), such as at least one disk memory.

[0124] Program 705 can be specifically called by processor 701 to enable electronic device 700 to execute the determination method operation of legal event determination information.

[0125] Some embodiments of the present application provide a computer-readable storage medium storing at least one executable instruction. When the executable instruction is executed on the electronic device 700, the electronic device 700 executes the method for determining the legal event determination information in the above-mentioned embodiment.

[0126] The executable instructions may be specifically used to enable the electronic device 700 to execute the method operation of determining the legal event determination information.

[0127] For example, the computer readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0128] The beneficial effects that can be achieved by the computer-readable storage medium provided in some embodiments of the present application can refer to the beneficial effects of the corresponding method for determining the legal event judgment information provided above, and will not be repeated here.

[0129] It should be noted that, in the application, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0130] Each embodiment in this specification is described in a related manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0131] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, which can be embodied in any computer-readable medium for use by an instruction execution system, apparatus or device (such as a computer-based system, a system including a processor or other system that can fetch instructions from an instruction execution system, apparatus or device and execute instructions), or used in combination with these instruction execution systems, apparatuses or devices.

[0132] For the purposes of this specification, a "computer-readable medium" can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by an instruction execution system, apparatus, or device or in conjunction with such instruction execution system, apparatus, or device.

[0133] More specific examples (a non-exhaustive list) of computer readable media include the following: an electrical connection having one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM).

[0134] In addition, the computer readable medium can even be a paper or other suitable medium on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, and then editing, interpreting or processing in other suitable ways as necessary, and then storing it in the computer memory. It should be understood that various parts of the present application can be implemented in hardware, software, firmware or a combination thereof.

[0135] In the above embodiments, multiple steps or methods may be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it may be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0136] The above-described embodiments of the present application do not constitute a limitation on the protection scope of the present application.

Claims

1. A method for determining legal event determination information, characterized in that: include: Acquire first event information corresponding to first question information input by a user, and determine a plurality of preset texts associated with the first event information in a preset database based on the first event information; Processing a first preset text to obtain a plurality of search pairs corresponding to the first preset text; wherein the first preset text is any preset text among the plurality of preset texts, and each of the plurality of search pairs includes a search identifier and a search content; Performing clustering processing on the multiple search pairs corresponding to the first preset text to obtain multiple candidate seed search pairs; Determine a target confidence score for each of the plurality of candidate seed search pairs; wherein the target confidence score is related to the degree of association between each of the candidate seed search pairs and the first event information, and the number of search pairs in the legal category corresponding to each of the candidate seed search pairs; Determine a candidate seed retrieval pair whose target confidence score is greater than or equal to a preset score among the multiple candidate seed retrieval pairs as a target seed retrieval pair; The search content of the target seed search pair is determined as the event determination information corresponding to the first question information.

2. The method according to claim 1, characterized in that The clustering process is performed on the multiple search pairs corresponding to the first preset text to obtain multiple candidate seed search pairs, including: In the clustering process of the current round, a plurality of first seed retrieval pairs obtained in the clustering process of the previous round and a plurality of unclustered first retrieval pairs are obtained; wherein the plurality of retrieval pairs include the plurality of first seed retrieval pairs and the plurality of first retrieval pairs, and the sum of the plurality of first seed retrieval pairs and the plurality of first retrieval pairs is equal to a preset number; Clustering the plurality of first seed search pairs and the plurality of first search pairs to obtain a plurality of second search pairs corresponding to each of the plurality of legal categories; Determine, among the plurality of second search pairs corresponding to the respective legal categories, a second seed search pair corresponding to each of the legal categories, and determine, among the plurality of search pairs, a plurality of unclustered second search pairs according to the preset number, the plurality of first search pairs, and the plurality of the second seed search pairs; In the next round of clustering, the multiple second seed retrieval pairs and the multiple second retrieval pairs are clustered until there are no unclustered retrieval pairs in the multiple retrieval pairs, and the multiple candidate seed retrieval pairs determined by the last round of clustering are obtained; wherein each of the multiple candidate seed retrieval pairs corresponds to a different legal category.

3. The method according to claim 2, characterized in that Determining, among the plurality of second search pairs corresponding to the legal categories, a second seed search pair corresponding to each legal category, comprises: In each of the legal categories, determining a semantic vector corresponding to each of the second search pairs; Determine the total distance between each first semantic vector and the second semantic vector in each legal category according to the semantic vector corresponding to each second search pair; wherein the first semantic vector is a semantic vector corresponding to any second search pair among the plurality of second search pairs corresponding to each legal category, and the second semantic vector is a semantic vector corresponding to a second search pair other than the second search pair corresponding to the first semantic vector; A target semantic vector having the shortest total distance to the second semantic vector is determined among the plurality of first semantic vectors, and a second retrieval pair corresponding to the target semantic vector is determined as the second seed retrieval pair corresponding to each of the legal categories.

4. The method according to claim 1, characterized in that Determining a target confidence score for each of the plurality of candidate seed retrieval pairs comprises: Determine a first confidence score for each candidate seed retrieval pair according to the degree of association between each candidate seed retrieval pair and the first event information; wherein the higher the degree of association between each candidate seed retrieval pair and the first event information, the higher the first confidence score for each candidate seed retrieval pair; Determine the number of search pairs in the legal category corresponding to each of the candidate seed search pairs, and determine the second confidence score of each of the candidate seed search pairs according to the number of search pairs corresponding to each of the candidate seed search pairs; wherein, the more the number of search pairs corresponding to each of the candidate seed search pairs, the higher the second confidence score of each of the candidate seed search pairs; Based on the first confidence score and the second confidence score of each of the candidate seed retrieval pairs, a target confidence score of each of the candidate seed retrieval pairs is determined.

5. The method according to claim 1, characterized in that The step of determining the search content of the target seed search pair as the event determination information corresponding to the first question information includes: If the ratio of the number of the target seed search pairs to the number of the plurality of candidate seed search pairs is greater than or equal to a preset ratio, the search content of the target seed search pairs is determined as the event determination information.

6. The method according to claim 5, characterized in that The method further comprises: If the ratio of the number of the target seed retrieval pairs to the number of the multiple candidate seed retrieval pairs is less than the preset ratio, and the number of times the clustering is executed in a loop is less than or equal to the preset number of executions, then the multiple retrieval pairs will continue to be clustered until the ratio of the number of the target seed retrieval pairs to the number of the multiple candidate seed retrieval pairs is greater than or equal to the preset ratio, or the number of times the clustering is executed in a loop is greater than the preset number of executions.

7. The method according to claim 6, characterized in that The method further comprises: If the number of times the clustering is executed in the loop is greater than the preset number of times, a second preset text among the multiple preset texts is processed to obtain multiple search pairs corresponding to the second preset text; wherein the second preset text is any preset text among the multiple preset texts except the first preset text; Clustering is performed on multiple search pairs corresponding to the second preset text to determine a target seed search pair corresponding to the second preset text, and the search content of the target seed search pair corresponding to the second preset text is determined as event determination information corresponding to the first question information.

8. The method according to any one of claims 1 to 7, characterized in that The event determination information is used to determine whether the first event information is established; if it is determined that the first event information is established, the first event information is the target event information corresponding to the first question information; In the case where it is impossible to determine whether the first event information is established, the event determination information is further used to determine the second question information to obtain the user's reply information to the second question information; The reply information is used to determine second event information corresponding to the first question information, and the second event information is target event information corresponding to the first question information.

9. A device for determining legal event judgment information, characterized in that: include: an acquisition module, configured to acquire first event information corresponding to first question information input by a user, and determine a plurality of preset texts associated with the first event information in a preset database based on the first event information; A processing module is configured to process a first preset text to obtain a plurality of search pairs corresponding to the first preset text; wherein the first preset text is any preset text among the plurality of preset texts, and each of the plurality of search pairs includes a search identifier and a search content; A clustering module, configured to perform clustering processing on a plurality of search pairs corresponding to the first preset text to obtain a plurality of candidate seed search pairs; A first determination module is configured to determine a target confidence score for each of the plurality of candidate seed retrieval pairs; wherein the target confidence score is related to a degree of association between each of the candidate seed retrieval pairs and the first event information, and the number of retrieval pairs in the legal category corresponding to each of the candidate seed retrieval pairs; A second determination module is configured to determine a candidate seed retrieval pair whose target confidence score is greater than or equal to a preset score among the plurality of candidate seed retrieval pairs as a target seed retrieval pair; The third determination module is configured to determine the search content of the target seed search pair as the event determination information corresponding to the first question information.

10. An electronic device, characterized in that: include: one or more processors; and A memory configured to: store one or more programs; Wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the method for determining legal event determination information according to any one of claims 1-8.

11. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the method for determining legal event determination information according to any one of claims 1-8 is implemented.

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