Incorporating non-local information into information extraction systems by Gibbs sampling
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Recognising textual entailment with logical inference
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Moses: open source toolkit for statistical machine translation
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
An inference model for semantic entailment in natural language
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Semantic inference at the lexical-syntactic level
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Simple coreference resolution with rich syntactic and semantic features
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
An efficient algorithm for easy-first non-directional dependency parsing
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
An open-source package for recognizing textual entailment
ACLDemos '10 Proceedings of the ACL 2010 System Demonstrations
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
Efficient search for transformation-based inference
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
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This paper introduces BiuTee, an open-source system for recognizing textual entailment. Its main advantages are its ability to utilize various types of knowledge resources, and its extensibility by which new knowledge resources and inference components can be easily integrated. These abilities make BiuTee an appealing RTE system for two research communities: (1) researchers of end applications, that can benefit from generic textual inference, and (2) RTE researchers, who can integrate their novel algorithms and knowledge resources into our system, saving the time and effort of developing a complete RTE system from scratch. Notable assistance for these researchers is provided by a visual tracing tool, by which researchers can refine and "debug" their knowledge resources and inference components.