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An Intelligent Legal Judgment Method of Numerical Perception Enhanced by Knowledge of Sentencing Standards

A standard and knowledgeable technology, applied in the field of artificial intelligence, can solve the problems of lack of perceived fines, sentence predictions, and inaccuracies in text values

Active Publication Date: 2022-07-08
SOUTHEAST UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a numerically-aware intelligent legal judgment method enhanced by the knowledge of sentencing standards, so as to solve the technical problems of inaccurate fines and sentence predictions caused by the lack of perception of textual values

Method used

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  • An Intelligent Legal Judgment Method of Numerical Perception Enhanced by Knowledge of Sentencing Standards
  • An Intelligent Legal Judgment Method of Numerical Perception Enhanced by Knowledge of Sentencing Standards
  • An Intelligent Legal Judgment Method of Numerical Perception Enhanced by Knowledge of Sentencing Standards

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Embodiment

[0060] Embodiment: the technical terms involved in the present invention are explained as follows

[0061] PTLM (Pre-Trained Language Model): Pre-trained language model

[0062] MNP (Masked Numeral Prediction): Masked Numerical Prediction

[0063] JKS (Judicial Knowledge Selection): Judicial Judgment Knowledge Selection

[0064] like figure 1 As shown, the present invention consists of four main modules: a JKS module, a legal digital meaning acquisition module based on MNP tasks, a graph network reasoning module and a judgment prediction module.

[0065] Firstly, a classifier based on contrastive learning is used to select the sentencing standard knowledge corresponding to a given crime fact. This module is the cornerstone of the entire model, which mimics the sentencing practice of judges. Only by using the correct knowledge of sentencing standards can an accurate judgment be made. The model then obtains legal numerical meanings from the knowledge of sentencing criteria...

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Abstract

The invention discloses an intelligent legal judgment method with numerical perception enhanced by the knowledge of sentencing standards, which is used to solve the problem that general methods lack numerical perception ability and thus perform poorly on numerical legal judgment tasks. The proposed method includes the following steps: firstly Use PTLM to encode factual descriptions to obtain sentence-level and word-level representations; then; then use Masked Numeric Prediction (MNP) based on a Pre-Trained Language Model (PTLM) to help the model obtain legal numerical meanings ; Then build a graph network from the numerical representation and the selected legal knowledge to perform numerical reasoning; finally, use the representation obtained through the above steps to predict the category. The present invention utilizes the advantages of PTLM in design, incorporates judicial priori, and constructs a graph network for numerical reasoning, which can significantly improve the accuracy of legal judgment.

Description

technical field [0001] The invention belongs to the field of artificial intelligence, and in particular relates to an intelligent legal judgment method of numerical perception enhanced by knowledge of sentencing standards. Background technique [0002] In recent years, legal artificial intelligence has attracted extensive attention from academia and industry. Earlier work often utilized mathematical and statistical algorithms to analyze existing legal cases. Inspired by the great success of deep learning, some researchers use knowledge of external legal terms or legal schematics as features to distinguish confusing cases. Some researchers have noticed the dependencies between the subtasks of Legal Judgment Prediction (LJP, Legal Judgment Prediction), and proposed a framework based on multi-task learning, which achieved excellent performance on two subtasks of LJP, namely, the and forecasts of legal terms. However, few methods focus on numerical LJP, the prediction of fine...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F40/30G06K9/62G06Q50/18G06F16/35
CPCG06F40/30G06F16/35G06Q50/18G06F18/214
Inventor 毕胜周之遥漆桂林
Owner SOUTHEAST UNIV
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