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Semantic parsing of ambiguous input through paraphrasing and verification

  • Philip Arthur
  • , Graham Neubig
  • , Sakriani Sakti
  • , Tomoki Toda
  • , Satoshi Nakamura

Research output: Contribution to journalArticleResearchpeer-review

Abstract

We propose a new method for semantic parsing of ambiguous and ungrammatical input, such as search queries. We do so by building on an existing semantic parsing framework that uses synchronous context free grammars (SCFG) to jointly model the input sentence and output meaning representation. We generalize this SCFG framework to allow not one, but multiple outputs. Using this formalism, we construct a grammar that takes an ambiguous input string and jointly maps it into both a meaning representation and a natural language paraphrase that is less ambiguous than the original input. This paraphrase can be used to disambiguate the meaning representation via verification using a language model that calculates the probability of each paraphrase.
Original languageEnglish
Pages (from-to)571-584
Number of pages14
JournalTransactions of the Association for Computational Linguistics
Volume3
DOIs
Publication statusPublished - 2015
Externally publishedYes

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