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28.01.2023 | Original Research

A novel MRC framework for evidence extracts in judgment documents

verfasst von: Yulin Zhou, Lijuan Liu, Yanping Chen, Ruizhang Huang, Yongbin Qin, Chuan Lin

Erschienen in: Artificial Intelligence and Law | Ausgabe 1/2024

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Abstract

Evidences are important proofs to support judicial trials. Automatically extracting evidences from judgement documents can be used to assess the trial quality and support “Intelligent Court”. Current evidence extraction is primarily depended on sequence labelling models. Despite their success, they can only assign a label to a token, which is difficult to recognize nested evidence entities in judgment documents, where a token may belong to several evidences at the same time. In this paper, we present a novel evidence extraction architecture called ATT-MRC, in which extracting evidence entities is formalized as a question answer problem, where all evidence spans are screened out as possible correct answers. Furthermore, to address the data imbalance problem in the judgement documents, we revised the loss function and combined it with a data enhancement technique. Experimental results demonstrate that our model has better performance than related works in evidence extraction.

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Metadaten
Titel
A novel MRC framework for evidence extracts in judgment documents
verfasst von
Yulin Zhou
Lijuan Liu
Yanping Chen
Ruizhang Huang
Yongbin Qin
Chuan Lin
Publikationsdatum
28.01.2023
Verlag
Springer Netherlands
Erschienen in
Artificial Intelligence and Law / Ausgabe 1/2024
Print ISSN: 0924-8463
Elektronische ISSN: 1572-8382
DOI
https://doi.org/10.1007/s10506-023-09344-z