Abstract
This paper presents a technique for the identification of participant slots in English language contracts. Taking inspiration from unsupervised slot extraction techniques, the system presented here uses a supervised approach to identify terms used to refer to a genre-specific slot in novel contracts. We evaluate the system in multiple feature configurations to demonstrate that the best performing system in both genres of contracts omits the exact mention form from consideration—even though such mention forms are often the name of the slot under consideration—and is instead based solely on the dependency label and parent; in other words, a more reliable quantification of a party’s role in a contract is found in what they do rather than what they are named.- Anthology ID:
- 2021.nllp-1.17
- Volume:
- Proceedings of the Natural Legal Language Processing Workshop 2021
- Month:
- November
- Year:
- 2021
- Address:
- Punta Cana, Dominican Republic
- Editors:
- Nikolaos Aletras, Ion Androutsopoulos, Leslie Barrett, Catalina Goanta, Daniel Preotiuc-Pietro
- Venue:
- NLLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 163–171
- Language:
- URL:
- https://aclanthology.org/2021.nllp-1.17
- DOI:
- 10.18653/v1/2021.nllp-1.17
- Cite (ACL):
- Dan Simonson. 2021. Supervised Identification of Participant Slots in Contracts. In Proceedings of the Natural Legal Language Processing Workshop 2021, pages 163–171, Punta Cana, Dominican Republic. Association for Computational Linguistics.
- Cite (Informal):
- Supervised Identification of Participant Slots in Contracts (Simonson, NLLP 2021)
- PDF:
- https://preview.aclanthology.org/corrections-2024-07/2021.nllp-1.17.pdf
- Data
- FrameNet