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Legal Information Retrieval and Entailment Based on BM25, Transformer and Semantic Thesaurus Methods
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Nature Singapore
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9075849/ https://www.ncbi.nlm.nih.gov/pubmed/35535319 http://dx.doi.org/10.1007/s12626-022-00103-1 |
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author | Kim, Mi-Young Rabelo, Juliano Okeke, Kingsley Goebel, Randy |
author_facet | Kim, Mi-Young Rabelo, Juliano Okeke, Kingsley Goebel, Randy |
author_sort | Kim, Mi-Young |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9075849 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Nature Singapore |
record_format | MEDLINE/PubMed |
spelling | pubmed-90758492022-05-07 Legal Information Retrieval and Entailment Based on BM25, Transformer and Semantic Thesaurus Methods Kim, Mi-Young Rabelo, Juliano Okeke, Kingsley Goebel, Randy Rev Socionetwork Strateg Article 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. Springer Nature Singapore 2022-02-07 2022 /pmc/articles/PMC9075849/ /pubmed/35535319 http://dx.doi.org/10.1007/s12626-022-00103-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Kim, Mi-Young Rabelo, Juliano Okeke, Kingsley Goebel, Randy Legal Information Retrieval and Entailment Based on BM25, Transformer and Semantic Thesaurus Methods |
title | Legal Information Retrieval and Entailment Based on BM25, Transformer and Semantic Thesaurus Methods |
title_full | Legal Information Retrieval and Entailment Based on BM25, Transformer and Semantic Thesaurus Methods |
title_fullStr | Legal Information Retrieval and Entailment Based on BM25, Transformer and Semantic Thesaurus Methods |
title_full_unstemmed | Legal Information Retrieval and Entailment Based on BM25, Transformer and Semantic Thesaurus Methods |
title_short | Legal Information Retrieval and Entailment Based on BM25, Transformer and Semantic Thesaurus Methods |
title_sort | legal information retrieval and entailment based on bm25, transformer and semantic thesaurus methods |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9075849/ https://www.ncbi.nlm.nih.gov/pubmed/35535319 http://dx.doi.org/10.1007/s12626-022-00103-1 |
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