DIRT @SBT@discovery of inference rules from text
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Methods for using textual entailment in open-domain question answering
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
NAACL-Short '06 Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers
The third PASCAL recognizing textual entailment challenge
RTE '07 Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing
Robust machine translation evaluation with entailment features
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 1 - Volume 1
Source-language entailment modeling for translating unknown terms
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
An extended model of natural logic
IWCS-8 '09 Proceedings of the Eighth International Conference on Computational Semantics
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
Constraints based taxonomic relation classification
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Defining specialized entailment engines using natural logic relations
LTC'09 Proceedings of the 4th conference on Human language technology: challenges for computer science and linguistics
Acquiring entailment pairs across languages and domains: a data analysis
IWCS '11 Proceedings of the Ninth International Conference on Computational Semantics
Towards component-based textual entailment
IWCS '11 Proceedings of the Ninth International Conference on Computational Semantics
Types of common-sense knowledge needed for recognizing textual entailment
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Unsupervised entailment detection between dependency graph fragments
BioNLP '11 Proceedings of BioNLP 2011 Workshop
Divide and conquer: crowdsourcing the creation of cross-lingual textual entailment corpora
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Evaluating language understanding accuracy with respect to objective outcomes in a dialogue system
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
Leveraging Diverse Lexical Resources for Textual Entailment Recognition
ACM Transactions on Asian Language Information Processing (TALIP) - Special Issue on RITE
A joint model for discovery of aspects in utterances
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Crowdsourcing inference-rule evaluation
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2
Semantic annotation for textual entailment recognition
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Computational Intelligence - Volume Part II
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We challenge the NLP community to participate in a large-scale, distributed effort to design and build resources for developing and evaluating solutions to new and existing NLP tasks in the context of Recognizing Textual Entailment. We argue that the single global label with which RTE examples are annotated is insufficient to effectively evaluate RTE system performance; to promote research on smaller, related NLP tasks, we believe more detailed annotation and evaluation are needed, and that this effort will benefit not just RTE researchers, but the NLP community as a whole. We use insights from successful RTE systems to propose a model for identifying and annotating textual inference phenomena in textual entailment examples, and we present the results of a pilot annotation study that show this model is feasible and the results immediately useful.