Large-scale Semantic Parsing without Question-Answer Pairs

Siva Reddy, Mirella Lapata, Mark Steedman


Abstract
In this paper we introduce a novel semantic parsing approach to query Freebase in natural language without requiring manual annotations or question-answer pairs. Our key insight is to represent natural language via semantic graphs whose topology shares many commonalities with Freebase. Given this representation, we conceptualize semantic parsing as a graph matching problem. Our model converts sentences to semantic graphs using CCG and subsequently grounds them to Freebase guided by denotations as a form of weak supervision. Evaluation experiments on a subset of the Free917 and WebQuestions benchmark datasets show our semantic parser improves over the state of the art.
Anthology ID:
Q14-1030
Volume:
Transactions of the Association for Computational Linguistics, Volume 2
Month:
Year:
2014
Address:
Cambridge, MA
Venue:
TACL
SIG:
Publisher:
MIT Press
Note:
Pages:
377–392
Language:
URL:
https://aclanthology.org/Q14-1030
DOI:
10.1162/tacl_a_00190
Bibkey:
Cite (ACL):
Siva Reddy, Mirella Lapata, and Mark Steedman. 2014. Large-scale Semantic Parsing without Question-Answer Pairs. Transactions of the Association for Computational Linguistics, 2:377–392.
Cite (Informal):
Large-scale Semantic Parsing without Question-Answer Pairs (Reddy et al., TACL 2014)
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PDF:
https://preview.aclanthology.org/update-css-js/Q14-1030.pdf