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Semantic lexicon acquisition for learning natural language interfaces
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ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
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COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
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Learning word meanings by instruction
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Using Multiple Clause Constructors in Inductive Logic Programming for Semantic Parsing
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EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
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Information Processing and Management: an International Journal
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This paper describes a system, WOLFIE (WOrd Learning From Interpreted Examples), that acquires a semantic lexicon from a corpus of sentences paired with semantic representations. The lexicon learned consists of words paired with meaning representations. WOLFIE is part of an integrated system that learns to parse novel sentences into semantic representations, such as logical database queries. Experimental results are presented demonstrating WOLFIE's ability to learn useful lexicons for a database interface in four different natural languages. The lexicons learned by WOLFIE are compared to those acquired by a similar system developed by Siskind (1996).