Integrating Multiple Knowledge Sources for Robust Semantic Parsing

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Sep 17, 2001
Jordi Atserias, Lluis Padro, German Rigau
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This work explores a new robust approach for Semantic Parsing of unrestricted texts. Our approach considers Semantic Parsing as a Consistent Labelling Problem (CLP), allowing the integration of several knowledge types (syntactic and semantic) obtained from different sources (linguistic and statistic). The current implementation obtains 95% accuracy in model identification and 72% in case-role filling.

* Proceedings of Euroconference on Recent Advances in Natural Language Processing (RANLP'01), p.8-14. Tzigov Chark, Bulgaria. Sept. 2001  
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