Abstract
We present a system to translate natural language sentences to formulas in a formal or a knowledge representation language. Our system uses two inverse λ-calculus operators and using them can take as input the semantic representation of some words, phrases and sentences and from that derive the semantic representation of other words and phrases. Our inverse λ operator works on many formal languages including first order logic, database query languages and answer set programming. Our system uses a syntactic combinatorial categorial parser to parse natural language sentences and also to construct the semantic meaning of the sentences as directed by their parsing. The same parser is used for both. In addition to the inverse λ-calculus operators, our system uses a notion of generalization to learn semantic representation of words from the semantic representation of other words that are of the same category. Together with this, we use an existing statistical learning approach to assign weights to deal with multiple meanings of words. Our system produces improved results on standard corpora on natural language interfaces for robot command and control and database queries.
Original language | English (US) |
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Title of host publication | Proceedings of the 9th International Conference on Computational Semantics, IWCS 2011 |
Publisher | Association for Computational Linguistics, ACL Anthology |
Pages | 35-44 |
Number of pages | 10 |
State | Published - Jan 1 2011 |
Event | 9th International Conference on Computational Semantics, IWCS 2011 - Oxford, United Kingdom Duration: Jan 12 2011 → Jan 14 2011 |
Other
Other | 9th International Conference on Computational Semantics, IWCS 2011 |
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Country/Territory | United Kingdom |
City | Oxford |
Period | 1/12/11 → 1/14/11 |
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Information Systems