TY - GEN
T1 - Automatic generation and scoring of positive interpretations from negated statements
AU - Blanco, Eduardo
AU - Sarabi, Zahra
N1 - Publisher Copyright:
©2016 Association for Computational Linguistics.
PY - 2016
Y1 - 2016
N2 - This paper presents a methodology to extract positive interpretations from negated statements. First, we automatically generate plausible interpretations using well-known grammar rules and manipulating semantic roles. Second, we score plausible alternatives according to their likelihood. Manual annotations show that the positive interpretations are intuitive to humans, and experimental results show that the scoring task can be automated.
AB - This paper presents a methodology to extract positive interpretations from negated statements. First, we automatically generate plausible interpretations using well-known grammar rules and manipulating semantic roles. Second, we score plausible alternatives according to their likelihood. Manual annotations show that the positive interpretations are intuitive to humans, and experimental results show that the scoring task can be automated.
UR - http://www.scopus.com/inward/record.url?scp=84994112053&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84994112053&partnerID=8YFLogxK
U2 - 10.18653/v1/n16-1169
DO - 10.18653/v1/n16-1169
M3 - Conference contribution
AN - SCOPUS:84994112053
T3 - 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2016 - Proceedings of the Conference
SP - 1431
EP - 1441
BT - 2016 Conference of the North American Chapter of the Association for Computational Linguistics
PB - Association for Computational Linguistics (ACL)
T2 - 15th Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2016
Y2 - 12 June 2016 through 17 June 2016
ER -