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Abstract
Weakly-supervised semantic parsers are trained on utterance-denotation pairs, treating logical forms as latent. The task is challenging due to the large search space and spuriousness of logical forms. In this paper we introduce a neural
parser-ranker system which addresses both challenges based on three innovations: (a) candidate (tree-structured) logical forms in our model are ranked based on two criteria, i.e., whether they are likely to execute to the correct denotation and the degree to which they preserve the meaning of the utterance; (b) a scheduled training procedure effectively balances the contribution of the two objectives; (c) a neurally encoded lexicon is used to inject prior domain knowledge to the model. Experiments on three Freebase datasets demonstrate the effectiveness of our semantic parser, achieving state-of-the-art results.
parser-ranker system which addresses both challenges based on three innovations: (a) candidate (tree-structured) logical forms in our model are ranked based on two criteria, i.e., whether they are likely to execute to the correct denotation and the degree to which they preserve the meaning of the utterance; (b) a scheduled training procedure effectively balances the contribution of the two objectives; (c) a neurally encoded lexicon is used to inject prior domain knowledge to the model. Experiments on three Freebase datasets demonstrate the effectiveness of our semantic parser, achieving state-of-the-art results.
Original language | English |
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Title of host publication | SIGNLL Conference on Computational Natural Language Learning (CoNLL 2018) |
Place of Publication | Brussels, Belgium |
Publisher | Association for Computational Linguistics |
Pages | 356-367 |
Number of pages | 12 |
Publication status | Published - Oct 2018 |
Event | SIGNLL Conference on Computational Natural Language Learning - Brussels, Belgium Duration: 31 Oct 2018 → 1 Nov 2018 http://www.conll.org/2018 |
Conference
Conference | SIGNLL Conference on Computational Natural Language Learning |
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Abbreviated title | CoNLL 2018 |
Country/Territory | Belgium |
City | Brussels |
Period | 31/10/18 → 1/11/18 |
Internet address |
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