Combining Logical and Distributional Semantics
The Field of Distributional Semantics provides techniques for reasoning about the meanings of words and phrases based on usage statistics in large text corpora; however, these techniques typically fail to capture much of the logical structure of natural language. Purely logic-based approaches to natural language semantics, on the other hand, fail to capture many graded notions of word meaning. We are investigating methods to combine these two approaches to natural language semantics.
I. Beltagy Ph.D. Alumni beltagy [at] cs utexas edu
Raymond J. Mooney Faculty mooney [at] cs utexas edu
Stephen Roller Ph.D. Student roller [at] cs utexas edu
Natural Language Semantics Using Probabilistic Logic 2016
I. Beltagy, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Representing Meaning with a Combination of Logical and Distributional Models 2016
I. Beltagy, Stephen Roller, Pengxiang Cheng, Katrin Erk, and Raymond J. Mooney, The special issue of Computational Linguistics on Formal Distributional Semantics, Vol. 42, 4 (2016).
On the Proper Treatment of Quantifiers in Probabilistic Logic Semantics 2015
I. Beltagy and Katrin Erk, In Proceedings of the 11th International Conference on Computational Semantics (IWCS-2015), London, UK, April 2015.
Efficient Markov Logic Inference for Natural Language Semantics 2014
I. Beltagy and Raymond J. Mooney, In Proceedings of the Fourth International Workshop on Statistical Relational AI at AAAI (StarAI-2014), pp. 9--14, Quebec City, Canada, July 2014.
Natural Language Semantics using Probabilistic Logic 2014
I. Beltagy, PhD proposal, Department of Computer Science, The University of Texas at Austin.
Probabilistic Soft Logic for Semantic Textual Similarity 2014
I. Beltagy, Katrin Erk, and Raymond J. Mooney, In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL-14), pp. 1210--1219, Baltimore, MD 2014.
Semantic Parsing using Distributional Semantics and Probabilistic Logic 2014
I. Beltagy, Katrin Erk, and Raymond Mooney, In Proceedings of ACL 2014 Workshop on Semantic Parsing (SP-2014), pp. 7--11, Baltimore, MD, June 2014.
UTexas: Natural Language Semantics using Distributional Semantics and Probabilistic Logic 2014
I. Beltagy, Stephen Roller, Gemma Boleda, and Katrin Erk, and Raymond J. Mooney, In The 8th Workshop on Semantic Evaluation (SemEval-2014), pp. 796--801, Dublin, Ireland, August 2014.
Montague Meets Markov: Deep Semantics with Probabilistic Logical Form 2013
I. Beltagy, Cuong Chau, Gemma Boleda, Dan Garrette, Katrin Erk, Raymond Mooney, Proceedings of the Second Joint Conference on Lexical and Computational Semantics (*Sem-2013) (2013), pp. 11--21.
Integrating Logical Representations with Probabilistic Information using Markov Logic 2011
Dan Garrette, Katrin Erk, Raymond Mooney, In Proceedings of the International Conference on Computational Semantics, pp. 105--114, Oxford, England, January 2011.