TY - GEN
T1 - Understanding negation in positive terms using syntactic dependencies
AU - Sarabi, Zahra
AU - Blanco, Eduardo
N1 - Publisher Copyright:
© 2016 Association for Computational Linguistics
PY - 2016
Y1 - 2016
N2 - This paper presents a two-step procedure to extract positive meaning from verbal negation. We first generate potential positive interpretations manipulating syntactic dependencies. Then, we score them according to their likelihood. Manual annotations show that positive interpretations are ubiquitous and intuitive to humans. Experimental results show that dependencies are better suited than semantic roles for this task, and automation is possible.
AB - This paper presents a two-step procedure to extract positive meaning from verbal negation. We first generate potential positive interpretations manipulating syntactic dependencies. Then, we score them according to their likelihood. Manual annotations show that positive interpretations are ubiquitous and intuitive to humans. Experimental results show that dependencies are better suited than semantic roles for this task, and automation is possible.
UR - http://www.scopus.com/inward/record.url?scp=85021631076&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85021631076&partnerID=8YFLogxK
U2 - 10.18653/v1/d16-1119
DO - 10.18653/v1/d16-1119
M3 - Conference contribution
AN - SCOPUS:85021631076
T3 - EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings
SP - 1108
EP - 1118
BT - EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings
PB - Association for Computational Linguistics (ACL)
T2 - 2016 Conference on Empirical Methods in Natural Language Processing, EMNLP 2016
Y2 - 1 November 2016 through 5 November 2016
ER -