Development of an Enterprise-Grade Contract Understanding System

被引：0

作者：

Agarwal, A. ^{[2
]}

Chiticariu, L. ^{[3
]}

Raman, P. Chozhiyath ^{[3
]}

Danilevsky, M. ^{[1
]}

Ghazi, D. ^{[5
]}

Gupta, A. ^{[2
]}

Guttula, S. ^{[2
]}

Katsis, Y. ^{[1
]}

Krishnamurthy, R. ^{[3
]}

Li, Y. ^{[1
]}

Mudgal, S. ^{[3
]}

Munigala, V ^{[2
]}

Phan, N. ^{[6
]}

Sonawane, D. ^{[3
]}

Srinivasan, S. ^{[3
]}

Thitte, S. ^{[3
]}

Vasa, M. ^{[3
]}

Venkatachalam, R. ^{[3
]}

Yaski, V ^{[4
]}

Zhu, H. ^{[1
]}

机构：

[1] IBM Res Almaden, San Jose, CA 95120 USA

[2] IBM Res India, Gurgaon, Haryana, India

[3] IBM Data & AI, Cambridge, MA USA

[4] Amazon, Seattle, WA USA

[5] Google LLC, Seattle, WA USA

[6] Visa, Foster City, CA USA

来源：

2021 CONFERENCE OF THE NORTH AMERICAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, NAACL-HLT 2021 | 2021年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Contracts are arguably the most important type of business documents. Despite their significance in business, legal contract review largely remains an arduous, expensive and manual process. In this paper, we describe the Transparent and Expert Contract Understanding System (TECUS): a commercial system designed and deployed for contract understanding and used by a wide range of enterprise users for the past few years. We reflect on the challenges and design decisions when building TECUS. We also summarize the data science life cycle of TECUS and share lessons learned.

引用

页码：222 / 229

页数：8

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