US 2022/0067076 A1Published application

Method and system for retrieval of prior court cases using witness testimonies

AssigneeTata Consultancy Services Limited

InventorsKripabandhu GHOSH, Sachin Sharad PAWAR, Girish Keshav PALSHIKAR, Pushpak BHATTACHARYYA, Vasudeva Varma KALIDINDI

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Abstract

This disclosure relates generally to retrieval of prior court cases using witness testimonies. Conventional state-of-the-art methods use supervised techniques for answering basic questions in legal domain using numerous features and do not address interpretability of results and the performance and precision of retrieving prior court cases for these methods are less. Embodiments of the present disclosure obtains an embedded representation for an event structure of a user query and testimony sentences identified from prior court cases using a trained Bi-LSTM classifier and a set of linguistic rules. A similarity is estimated between the embedded representation for the event structure of the user query and the event structure of each testimony sentence from the prior court cases. Further a relevance score is assigned in accordance with the estimated similarity to retrieve the relevant prior court cases. The disclosed method is used to retrieve the relevant prior court cases using witness testimonies.

Claims15

Dependent claims

A processor implemented method for retrieving one or more prior court cases using witness testimonies, the method comprising:

receiving, via one or more hardware processors, a user query for retrieving one or more prior court cases, wherein the one or more prior court cases comprise a set of testimony sentences and a set of non-testimony sentences, wherein the user query and each testimony sentence of the set of testimony sentences comprise an event structure with a predicate and one or more arguments;
obtaining an embedded representation for the event structure of the user query, using a trained denoising auto-encoder executed via the one or more hardware processors, wherein the denoising auto-encoder is trained using one or more testimony sentences from the set of testimony sentences wherein the one or more testimony sentences are identified using a trained classifier and a set of linguistic rules;
estimating, via the one or more hardware processors, a similarity between the obtained embedded representation of the user query and an embedded representation of each of the one or more testimony sentences using a similarity function;
assigning a relevance score, via the one or more hardware processors, to the one or more prior court cases associated with the one or more testimony sentences in accordance with the estimated similarity;
and
retrieving a predefined number of prior court cases out of the one or more prior court cases, wherein the predefined number is decided based on the assigned relevance score.

3 more elements

A system (100), comprising:

a memory (104) storing instructions;
one or more communication interfaces (106);
and
one or more hardware processors (102) coupled to the memory (104) via the one or more communication interfaces (106), wherein the one or more hardware processors (102) are configured by the instructions to:
receive a user query for retrieving one or more prior court cases, wherein the one or more prior court cases comprise a set of testimony sentences and a set of non-testimony sentences, wherein the user query and each testimony sentence of the set of testimony sentences comprise an event structure with a predicate and one or more arguments;
obtain an embedded representation for the event structure of the user query, using a trained denoising auto-encoder, wherein the denoising auto-encoder is trained using one or more testimony sentences from the set of testimony sentences wherein the one or more testimony sentences are identified using a trained classifier and a set of linguistic rules;
estimate a similarity between the obtained embedded representation of the user query and an embedded representation of each of the one or more testimony sentences using a similarity function;
assign a relevance score to the one or more prior court cases associated with the one or more testimony sentences in accordance with the estimated similarity;
and
retrieve a predefined number of prior court cases out of the one or more prior court cases, wherein the predefined number is decided based on the assigned relevance score.

7 more elements

Dependencies are inferred from the claim text.