Discovery of inference rules for question-answering
Natural Language Engineering
Robust textual inference via graph matching
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
A logic-based semantic approach to recognizing textual entailment
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
An inference model for semantic entailment in natural language
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Robust textual inference via learning and abductive reasoning
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
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 phrase-based alignment model for natural language inference
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Inferring textual entailment with a probabilistically sound calculus*
Natural Language Engineering
Semantic inference at the lexical-syntactic level for textual entailment recognition
RTE '07 Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing
A compact forest for scalable inference over entailment and paraphrase rules
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Natural language as the basis for meaning representation and inference
CICLing'08 Proceedings of the 9th international conference on Computational linguistics and intelligent text processing
Syntactic/semantic structures for textual entailment recognition
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Assessing the role of discourse references in entailment inference
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Exemplar-based models for word meaning in context
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
A survey of paraphrasing and textual entailment methods
Journal of Artificial Intelligence Research
Learning entailment relations by global graph structure optimization
Computational Linguistics
Modality and negation in simt use of modality and negation in semantically-informed syntactic mt
Computational Linguistics
Inferring the semantic properties of sentences by mining syntactic parse trees
Data & Knowledge Engineering
BiuTee: a modular open-source system for recognizing textual entailment
ACL '12 Proceedings of the ACL 2012 System Demonstrations
Efficient search for transformation-based inference
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Statistical modality tagging from rule-based annotations and crowdsourcing
ExProM '12 Proceedings of the Workshop on Extra-Propositional Aspects of Meaning in Computational Linguistics
Machine learning of syntactic parse trees for search and classification of text
Engineering Applications of Artificial Intelligence
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Semantic inference is an important component in many natural language understanding applications. Classical approaches to semantic inference rely on complex logical representations. However, practical applications usually adopt shallower lexical or lexical-syntactic representations, but lack a principled inference framework. We propose a generic semantic inference framework that operates directly on syntactic trees. New trees are infened by applying entailment rules, which provide a unified representation for varying types of inferences. Rules were generated by manual and automatic methods, Covering generic linguistic structures as well as specific lexical-based inferences. Initial empirical evaluation in a Relation Extraction setting supports the validity of our approach.