Legal Information Retrieval and Entailment Based on BM25, Transformer and Semantic Thesaurus Methods

Mi-Young Kim (), Juliano Rabelo (), Kingsley Okeke () and Randy Goebel ()
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Mi-Young Kim: University of Alberta
Juliano Rabelo: University of Alberta
Kingsley Okeke: University of Alberta
Randy Goebel: University of Alberta

The Review of Socionetwork Strategies, 2022, vol. 16, issue 1, 157-174

Abstract: Abstract We describe the techniques applied by the University of Alberta (UA) team in the most recent Competition on Legal Information Extraction and Entailment (COLIEE 2021). We participated in retrieval and entailment tasks for both case law and statute law; we applied a transformer-based approach for the case law entailment task, an information retrieval technique based on BM25 for legal information retrieval, and a natural language inference mechanism using semantic knowledge applied to statute law texts. This competition included 25 teams from 14 countries; our case law entailment approach was ranked no. 4 in Task 2, the BM25 technique for legal information retrieval was ranked no. 3 in Task 3, and the natural language inference technique incorporating semantic information was ranked no. 4 in Task 4. The combination of the latter two techniques on Task 5 was ranked no. 2. We also performed error analysis of our system in Task 4, which provides some insight into current state-of-the-art and research priorities for future directions.

Keywords: Legal Information Extraction; Legal Information Entailment; BM25; Transformers; 68T50; 68T07; 68T05 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s12626-022-00103-1

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