Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
ACL '85 Proceedings of the 23rd annual meeting on Association for Computational Linguistics
Computational Semantics in Discourse: Underspecification, Resolution, and Inference
Journal of Logic, Language and Information
Feature-rich part-of-speech tagging with a cyclic dependency network
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Wide-coverage efficient statistical parsing with ccg and log-linear models
Computational Linguistics
Modeling semantic containment and exclusion in natural language inference
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Personalizing PageRank for word sense disambiguation
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
SemEval-2007 task 16: evaluation of wide coverage knowledge resources
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Augmenting WordNet for deep understanding of text
STEP '08 Proceedings of the 2008 Conference on Semantics in Text Processing
The third PASCAL recognizing textual entailment challenge
RTE '07 Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing
On the role of lexical and world knowledge in RTE3
RTE '07 Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing
The PASCAL recognising textual entailment challenge
MLCW'05 Proceedings of the First international conference on Machine Learning Challenges: evaluating Predictive Uncertainty Visual Object Classification, and Recognizing Textual Entailment
Recognising textual entailment with robust logical inference
MLCW'05 Proceedings of the First international conference on Machine Learning Challenges: evaluating Predictive Uncertainty Visual Object Classification, and Recognizing Textual Entailment
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This paper presents an automatically generated Intermediate Logic Form of WordNet's glosses. Our proposed logic form includes neo-Davidsonian reification in a simple and flat syntax close to natural language. We offer a comparison with other semantic representations such as those provided by Hobbs and Extended WordNet. The Intermediate Logic Forms are straightforwardly obtained from the output of a pipeline consisting of a part-of-speech tagger, a dependency parser and our own Intermediate Logic Form generator (all freely available tools). We apply the pipeline to the glosses of WordNet 3.0 to obtain a lexical resource ready to be used as knowledge base or resource for a variety of tasks involving some kind of semantic inference. We present a qualitative evaluation of the resource and discuss its possible application in Natural Language Understanding.