DIRT @SBT@discovery of inference rules from text
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Parsing engineering and empirical robustness
Natural Language Engineering
Extracting paraphrases from a parallel corpus
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
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
A machine learning approach to textual entailment recognition
Natural Language Engineering
Learning textual entailment on a distance feature space
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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Recognition of textual entailment is not an easy task. In fact, early experimental evidences in [1] seems to demonstrate that even human judges often fail in reaching an agreement on the existence of entailment relation between two expressions. We aim to contribute to the theoretical and practical setting of textual entailment, through both a linguistic inspection of the textual entailment phenomenon and the description of a new promising approach to recognition, as implemented in the system we proposed at the RTE competition [2].