@inproceedings{6d10314856924650aca244abd911fa63,
title = "BERT-Based Ensemble Model for Statute Law Retrieval and Legal Information Entailment",
abstract = "The Competition on legal information extraction/entailment (COLIEE) is an international information processing and retrieval competition. As an aid to future participants as well as question designers, this article describes how to connect legal questions taken from past Japanese bar exams to relevant statutes (articles of the Japanese Civil Code, Task 3) and how to construct a Yes/No question answering system for legal queries (Task 4) incorporating background materials on Japanese law. We restructured the given data to a dataset which contains all possible combinations of queries and articles as continuous strings as our samples. In this way, the difficult pairing task has been turned into a simpler classification task and samples for training became sufficient in number. Next, we used three BERT-based models to solve binary questions in order to achieve stable performance. As a result, the model achieved an F2-score of 0.6587 in Task 3 (ranked 1st) and an accuracy of 0.6161 in Task 4.",
keywords = "BERT-based ensemble model, COLIEE 2020, Information retrieval, Legal AI, Legal analytics, Textual entailment",
author = "Shao, {Hsuan Lei} and Chen, {Yi Chia} and Huang, {Sieh Chuen}",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 12th International Symposium on Artificial Intelligence supported by the Japanese Society for Artificial Intelligence, JSAI-isAI 2020, International Workshop on Logic and Engineering of Natural Language Semantics, LENLS 2020, 14th International Workshop on Juris-informatics, JURISIN 2020 ; Conference date: 15-11-2020 Through 17-11-2020",
year = "2021",
doi = "10.1007/978-3-030-79942-7_15",
language = "English",
isbn = "9783030799410",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "226--239",
editor = "Naoaki Okazaki and Katsutoshi Yada and Ken Satoh and Koji Mineshima",
booktitle = "New Frontiers in Artificial Intelligence - JSAI-isAI 2020 Workshops, JURISIN, LENLS 2020 Workshops, 2020, Revised Selected Papers",
}