Abstract
HUKB group is participating in the Statute Law task (Tasks 3 and 4) in COLIEE 2022. For Task 3, we propose a method that utilizes three different IR systems. Our new proposed IR system utilizes the similarity of descriptions of judicial decisions between questions and articles. In addition to this new IR system, we also use an ordinal keyword-based IR system (BM25) and the BERT-based IR system proposed in COLIEE 2020. Because of the different characteristics of these systems, ensembled results have better recall without losing too much precision. Our system, which ensembles the results of our new proposed IR and keyword-based IR system, achieves the best performance for Task 3. For Task 4, we extend our previous BERT-based entailment system (the best performance system of COLIEE 2021) by using a new data augmentation method and a method to select relevant parts from the articles. We discuss the characteristics of the system using the submitted results.
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This work was partially supported by JSPS KAKENHI Grant Number 18H0333808.
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Yoshioka, M., Suzuki, Y., Aoki, Y. (2023). HUKB at the COLIEE 2022 Statute Law Task. In: Takama, Y., Yada, K., Satoh, K., Arai, S. (eds) New Frontiers in Artificial Intelligence. JSAI-isAI 2022. Lecture Notes in Computer Science(), vol 13859. Springer, Cham. https://doi.org/10.1007/978-3-031-29168-5_8
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