DIRT @SBT@discovery of inference rules from text
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Discovery of inference rules for question-answering
Natural Language Engineering
Learning to paraphrase: an unsupervised approach using multiple-sequence alignment
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Paraphrase acquisition for information extraction
PARAPHRASE '03 Proceedings of the second international workshop on Paraphrasing - Volume 16
Sentence alignment for monolingual comparable corpora
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Unsupervised construction of large paraphrase corpora: exploiting massively parallel news sources
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
The distributional similarity of sub-parses
EMSEE '05 Proceedings of the ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment
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
What syntax can contribute in the entailment task
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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The Computational Linguistics at Concordia laboratory system for textual entailment determination is based on shallow, partial predicate-argument structure matching combined with a WordNet-based lexical similarity measure. In this paper we describe experiments with different system settings conducted to assess the potential and limitations of partial predicate-argument structures in textual entailment determination.