TY - GEN
T1 - Conversion of Legal Agreements into Smart Legal Contracts using NLP
AU - Chen, Eason
AU - Roche, Niall
AU - Tseng, Yuen Hsien
AU - Hernandez, Walter
AU - Shangguan, Jiangbo
AU - Moore, Alastair
N1 - Funding Information:
This work received support from Google Summer of Code and was partially supported by the Ministry of Science and Technology of Taiwan (R.O.C.) under Grant 109-2410-H-003-123-MY3. We express our gratitude to the Accord Project’s members, particularly, Matt Roberts, Jérôme Siméon, and Dan Selman for their assistance with this project.
Publisher Copyright:
© 2023 ACM.
PY - 2023/4/30
Y1 - 2023/4/30
N2 - A Smart Legal Contract (SLC) is a specialized digital agreement comprising natural language and computable components. The Accord Project provides an open-source SLC framework containing three main modules: Cicero, Concerto, and Ergo. Currently, we need lawyers, programmers, and clients to work together with great effort to create a usable SLC using the Accord Project. This paper proposes a pipeline to automate the SLC creation process with several Natural Language Processing (NLP) models to convert law contracts to the Accord Project's Concerto model. After evaluating the proposed pipeline, we discovered that our NER pipeline accurately detects CiceroMark from Accord Project template text with an accuracy of 0.8. Additionally, our Question Answering method can extract one-third of the Concerto variables from the template text. We also delve into some limitations and possible future research for the proposed pipeline. Finally, we describe a web interface enabling users to build SLCs. This interface leverages the proposed pipeline to convert text documents to Smart Legal Contracts by using NLP models.
AB - A Smart Legal Contract (SLC) is a specialized digital agreement comprising natural language and computable components. The Accord Project provides an open-source SLC framework containing three main modules: Cicero, Concerto, and Ergo. Currently, we need lawyers, programmers, and clients to work together with great effort to create a usable SLC using the Accord Project. This paper proposes a pipeline to automate the SLC creation process with several Natural Language Processing (NLP) models to convert law contracts to the Accord Project's Concerto model. After evaluating the proposed pipeline, we discovered that our NER pipeline accurately detects CiceroMark from Accord Project template text with an accuracy of 0.8. Additionally, our Question Answering method can extract one-third of the Concerto variables from the template text. We also delve into some limitations and possible future research for the proposed pipeline. Finally, we describe a web interface enabling users to build SLCs. This interface leverages the proposed pipeline to convert text documents to Smart Legal Contracts by using NLP models.
KW - Blockchain
KW - Domain Specific Language
KW - Human-AI collaboration
KW - Information Retrieval
KW - Smart Legal Contract
UR - http://www.scopus.com/inward/record.url?scp=85159597466&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85159597466&partnerID=8YFLogxK
U2 - 10.1145/3543873.3587554
DO - 10.1145/3543873.3587554
M3 - Conference contribution
AN - SCOPUS:85159597466
T3 - ACM Web Conference 2023 - Companion of the World Wide Web Conference, WWW 2023
SP - 1112
EP - 1118
BT - ACM Web Conference 2023 - Companion of the World Wide Web Conference, WWW 2023
PB - Association for Computing Machinery, Inc
T2 - 2023 World Wide Web Conference, WWW 2023
Y2 - 30 April 2023 through 4 May 2023
ER -