A Notion of Semantic Coherence for Underspecified Semantic Representation

Mehdi Manshadi, Daniel Gildea, James F. Allen


Abstract
The general problem of finding satisfying solutions to constraint-based underspecified representations of quantifier scope is NP-complete. Existing frameworks, including Dominance Graphs, Minimal Recursion Semantics, and Hole Semantics, have struggled to balance expressivity and tractability in order to cover real natural language sentences with efficient algorithms. We address this trade-off with a general principle of coherence, which requires that every variable introduced in the domain of discourse must contribute to the overall semantics of the sentence. We show that every underspecified representation meeting this criterion can be efficiently processed, and that our set of representations subsumes all previously identified tractable sets.
Anthology ID:
J18-1003
Volume:
Computational Linguistics, Volume 44, Issue 1 - April 2018
Month:
April
Year:
2018
Address:
Cambridge, MA
Venue:
CL
SIG:
Publisher:
MIT Press
Note:
Pages:
39–83
Language:
URL:
https://aclanthology.org/J18-1003
DOI:
10.1162/COLI_a_00307
Bibkey:
Cite (ACL):
Mehdi Manshadi, Daniel Gildea, and James F. Allen. 2018. A Notion of Semantic Coherence for Underspecified Semantic Representation. Computational Linguistics, 44(1):39–83.
Cite (Informal):
A Notion of Semantic Coherence for Underspecified Semantic Representation (Manshadi et al., CL 2018)
Copy Citation:
PDF:
https://aclanthology.org/J18-1003.pdf