Abstract
This paper presents an open-source toolkit for negation detection. It identifies negation cues and their corresponding scope in either raw or parsed text using maximum-margin classification. The system design draws on best practice from the existing literature on negation detection, aiming for a simple and portable system that still achieves competitive performance. Pre-trained models and experimental results are provided for English.- Anthology ID:
- W17-1810
- Volume:
- Proceedings of the Workshop Computational Semantics Beyond Events and Roles
- Month:
- April
- Year:
- 2017
- Address:
- Valencia, Spain
- Editors:
- Eduardo Blanco, Roser Morante, Roser Saurí
- Venue:
- SemBEaR
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 64–69
- Language:
- URL:
- https://aclanthology.org/W17-1810
- DOI:
- 10.18653/v1/W17-1810
- Cite (ACL):
- Martine Enger, Erik Velldal, and Lilja Øvrelid. 2017. An open-source tool for negation detection: a maximum-margin approach. In Proceedings of the Workshop Computational Semantics Beyond Events and Roles, pages 64–69, Valencia, Spain. Association for Computational Linguistics.
- Cite (Informal):
- An open-source tool for negation detection: a maximum-margin approach (Enger et al., SemBEaR 2017)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/W17-1810.pdf
- Code
- marenger/negtool