LexRel: Benchmarking Legal Relation Extraction for Chinese Civil Cases

Fuente: arXiv
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Main Authors: Cai, Yida, Hu, Ranjuexiao, Xie, Huiyuan, Li, Chenyang, Liu, Yun, Ye, Yuxiao, Liu, Zhenghao, Shen, Weixing, Liu, Zhiyuan
Format: Preprint
Published: 2025
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author Cai, Yida
Hu, Ranjuexiao
Xie, Huiyuan
Li, Chenyang
Liu, Yun
Ye, Yuxiao
Liu, Zhenghao
Shen, Weixing
Liu, Zhiyuan
author_facet Cai, Yida
Hu, Ranjuexiao
Xie, Huiyuan
Li, Chenyang
Liu, Yun
Ye, Yuxiao
Liu, Zhenghao
Shen, Weixing
Liu, Zhiyuan
contents Legal relations serve as an important analytical framework for dispute resolution in civil cases. However, legal relations in Chinese civil cases remain underexplored in the field of legal AI, largely due to the absence of comprehensive schemas. In this work, we first introduce a comprehensive schema for legal relations in civil cases, which contains a hierarchical taxonomy and definitions of arguments. Based on this schema, we formulate a legal relation extraction task and present LexRel, an expert-annotated benchmark for legal relation extraction in the Chinese civil law domain. We use LexRel to evaluate state-of-the-art large language models (LLMs) on legal relation extraction, showing that current LLMs exhibit significant limitations in accurately identifying civil legal relations. Furthermore, we demonstrate that explicitly incorporating information about legal relations leads to promising performance gains on other downstream legal AI tasks.
format Preprint
id arxiv_https___arxiv_org_abs_2512_12643
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle LexRel: Benchmarking Legal Relation Extraction for Chinese Civil Cases
Cai, Yida
Hu, Ranjuexiao
Xie, Huiyuan
Li, Chenyang
Liu, Yun
Ye, Yuxiao
Liu, Zhenghao
Shen, Weixing
Liu, Zhiyuan
Computation and Language
Legal relations serve as an important analytical framework for dispute resolution in civil cases. However, legal relations in Chinese civil cases remain underexplored in the field of legal AI, largely due to the absence of comprehensive schemas. In this work, we first introduce a comprehensive schema for legal relations in civil cases, which contains a hierarchical taxonomy and definitions of arguments. Based on this schema, we formulate a legal relation extraction task and present LexRel, an expert-annotated benchmark for legal relation extraction in the Chinese civil law domain. We use LexRel to evaluate state-of-the-art large language models (LLMs) on legal relation extraction, showing that current LLMs exhibit significant limitations in accurately identifying civil legal relations. Furthermore, we demonstrate that explicitly incorporating information about legal relations leads to promising performance gains on other downstream legal AI tasks.
title LexRel: Benchmarking Legal Relation Extraction for Chinese Civil Cases
topic Computation and Language
url https://arxiv.org/abs/2512.12643