Presentation information

Organized Session

Organized Session » OS-8

[4P3-OS-8] OS-8

Fri. Jun 12, 2020 2:00 PM - 3:40 PM Room P (jsai2020online-16)

加藤 恒昭(東京大学)、外山 勝彦(名古屋大学)、森 信介(京都大学)

2:40 PM - 3:00 PM

[4P3-OS-8-03] Extraction of important features for risk prediction in contracts

〇Tomohiko Abe1, Mina Fujii1, Hiromu Morita1, Yasuhiro Iwaki1, Tsuneaki Kato2 (1. GVA TECH K.K., 2. Graduate School of Arts and Sciences, The University of Tokyo)

Keywords:Machine Learning, Natural Language Processing, LegalTech, Interpretability, Explainability

Contract review requires legal knowledge, which makes it difficult for non-experts while easy for experts in the legal department. To overcome such legal disparity, we need to automate the review process, especially risk decision in contracts. In this paper, we formulate risk decision in contracts as binary text classification, train classifiers using machine learning models and evaluate them. To identify a text span to be revised in a contract, we apply LIME, a method for estimating important features for prediction, to BERT classifier and extract important tokens from text. It is observed that the extracted tokens match most of the gold ones annotated by experts. Furthermore, we present revision examples that result in the inverted risk prediction and contribute to the prediction. We show that LIME can help to identify a text span to be revised in review work and present correction examples with high transparency.

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