TY - GEN
T1 - Evaluating induced CCG parsers on grounded semantic parsing
AU - Bisk, Yonatan
AU - Reddy, Siva
AU - Blitzer, John
AU - Hockenmaier, Julia
AU - Steedman, Mark
N1 - Funding Information:
This paper is partly based on work that was done when the first and second authors were interns at Google, and on work that that was supported by NSF grant 1053856 to JH, and a Google PhD Fellowship to SR.
Publisher Copyright:
© 2016 Association for Computational Linguistics
PY - 2016
Y1 - 2016
N2 - We compare the effectiveness of four different syntactic CCG parsers for a semantic slot-filling task to explore how much syntactic supervision is required for downstream semantic analysis. This extrinsic, task-based evaluation also provides a unique window into the semantics captured (or missed) by unsupervised grammar induction systems.
AB - We compare the effectiveness of four different syntactic CCG parsers for a semantic slot-filling task to explore how much syntactic supervision is required for downstream semantic analysis. This extrinsic, task-based evaluation also provides a unique window into the semantics captured (or missed) by unsupervised grammar induction systems.
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U2 - 10.18653/v1/d16-1214
DO - 10.18653/v1/d16-1214
M3 - Conference contribution
AN - SCOPUS:85040913652
T3 - EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings
SP - 2022
EP - 2027
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 -