Knowledge representation: logical, philosophical and computational foundations
Knowledge representation: logical, philosophical and computational foundations
Logic for Problem Solving
Concurrent constraint programming languages
Concurrent constraint programming languages
The problem of logical-form equivalence
Computational Linguistics - Special issue on using large corpora: I
Comlex Syntax: building a computational lexicon
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
Learning constraint-based grammars from representative examples: theory and applications
Learning constraint-based grammars from representative examples: theory and applications
NAACL-Short '06 Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers
Learning to map text to graph-based meaning representations via grammar induction
TextGraphs-3 Proceedings of the 3rd Textgraphs Workshop on Graph-Based Algorithms for Natural Language Processing
Question answering using ontological semantics
TextMean '04 Proceedings of the 2nd Workshop on Text Meaning and Interpretation
Learning context-dependent mappings from sentences to logical form
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
A statistical semantic parser that integrates syntax and semantics
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Introduction to the CoNLL-2005 shared task: semantic role labeling
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
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We present an ontology-based semantic interpreter that can be linked to a grammar through grammar rule constraints, providing access to meaning during parsing and generation. In this approach, the parser will take as input natural language utterances and will produce ontology-based semantic representations. We rely on a recently developed constraint-based grammar formalism, which balances expressiveness with practical learnability results. We show that even with a weak “ontological model”, the semantic interpreter at the grammar rule level can help remove erroneous parses obtained when we do not have access to meaning.