TY - GEN
T1 - Predicting the focus of negation
T2 - 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020
AU - Hossain, Md Mosharaf
AU - Hamilton, Kathleen
AU - Palmer, Alexis
AU - Blanco, Eduardo
N1 - Funding Information:
Thanks to the anonymous reviewers for their insightful comments. This material is based upon work supported by the NSF under Grant No. 1845757. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF. The Titan Xp used for this research was donated by the NVIDIA Corporation. Computational resources were also provided by the UNT office of High-Performance Computing.
Publisher Copyright:
© 2020 Association for Computational Linguistics
PY - 2020
Y1 - 2020
N2 - The focus of a negation is the set of tokens intended to be negated, and a key component for revealing affirmative alternatives to negated utterances. In this paper, we experiment with neural networks to predict the focus of negation. Our main novelty is leveraging a scope detector to introduce the scope of negation as an additional input to the network. Experimental results show that doing so obtains the best results to date. Additionally, we perform a detailed error analysis providing insights into the main error categories, and analyze errors depending on whether the model takes into account scope and context information.
AB - The focus of a negation is the set of tokens intended to be negated, and a key component for revealing affirmative alternatives to negated utterances. In this paper, we experiment with neural networks to predict the focus of negation. Our main novelty is leveraging a scope detector to introduce the scope of negation as an additional input to the network. Experimental results show that doing so obtains the best results to date. Additionally, we perform a detailed error analysis providing insights into the main error categories, and analyze errors depending on whether the model takes into account scope and context information.
UR - https://www.scopus.com/pages/publications/85098426722
UR - https://www.scopus.com/pages/publications/85098426722#tab=citedBy
M3 - Conference contribution
AN - SCOPUS:85098426722
T3 - Proceedings of the Annual Meeting of the Association for Computational Linguistics
SP - 8389
EP - 8401
BT - ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference
PB - Association for Computational Linguistics (ACL)
Y2 - 5 July 2020 through 10 July 2020
ER -