Abstract:
In this paper we present the results of the Interactive Argument-Pair Extraction in Judgement Document
Challenge held by both the Chinese AI and Law Challenge (CAIL) and the Chinese National Social Media
Processing Conference (SMP), and introduce the related data set – SMP-CAIL2020-Argmine. The task
challenged participants to choose the correct argument among five candidates proposed by the defense to
refute or acknowledge the given argument made by the plaintiff, providing the full context recorded in the
judgement documents of both parties. We received entries from 63 competing teams, 38 of which scored
higher than the provided baseline model (BERT) in the first phase and entered the second phase. The best
performing system in the two phases achieved accuracy of 0.856 and 0.905, respectively. In this paper, we
will present the results of the competition and a summary of the systems, highlighting commonalities and
innovations among participating systems. The SMP-CAIL2020-Argmine data set and baseline models have
been already released.
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Subject:
Computer Science
>>
Integration Theory of Computer Science
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Cite as:
ChinaXiv:202211.00394
(or this version
ChinaXiv:202211.00394V1)
DOI:10.1162/dint_a_00094
CSTR:32003.36.ChinaXiv.202211.00394.V1
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TXID:
7e3a4435-94f4-4a48-92d2-a706afad7f6b
- Recommended references:
Jian, Yuan,Zhongyu, Wei,Yixu, Gao,Wei, Chen,Yun, Song,Donghua, Zhao,Jinglei, Ma,Zhen, Hu,Shaokun, Zou,Donghai, Li,Xuanjing, Huang.Overview of SMP-CAIL2020-Argmine: The Interactive Argument-Pair Extraction in Judgement Document Challenge.中国科学院科技论文预发布平台.[DOI:10.1162/dint_a_00094]
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