An open-source tool for negation detection: a maximum-margin approach

Martine Enger, Erik Velldal, Lilja Øvrelid


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
Venues:
SemBEaR | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
64–69
Language:
URL:
https://www.aclweb.org/anthology/W17-1810
DOI:
10.18653/v1/W17-1810
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PDF:
http://aclanthology.lst.uni-saarland.de/W17-1810.pdf