We propose deep learning based methods for automatic systems of legal retrieval and legal question-answering in COLIEE 2020. These systems are all characterized by being pre-trained on large amounts of data before being finetuned for the specified tasks. This approach helps to overcome the data scarcity and achieve good performance, thus can be useful for tackling related problems in information retrieval, and decision support in the legal domain. Besides, the approach can be explored to deal with other domain specific problems.
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References (12)
07Question answering system for legal bar examination using predicate argument structures focusing on exceptions2019
08Statutory entailment using similarity features and decomposable attention models2019
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11We enhance the system in the setting 1 by finetuning the supporting model on the training data of Task 2
12We directly use the already trained supporting model in Task 1 together with BM25 scoring for finding the support paragraphs for given entailed fragment