Readings in natural language processing
From English to logic: context-free computation of “conventional” logical translations
Readings in natural language processing
Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
DIRT @SBT@discovery of inference rules from text
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
ACL '88 Proceedings of the 26th annual meeting on Association for Computational Linguistics
COGEX: a logic prover for question answering
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Towards light semantic processing for Question Answering
HLT-NAACL-TEXTMEANING '03 Proceedings of the HLT-NAACL 2003 workshop on Text meaning - Volume 9
The Description Logic Handbook
The Description Logic Handbook
Semantic role labeling via integer linear programming inference
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Adding predicate argument structure to the Penn TreeBank
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Identification and tracing of ambiguous names: discriminative and generative approaches
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
The necessity of syntactic parsing for semantic role labeling
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Learning with feature description logics
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
Learning to recognize features of valid textual entailments
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
A logic-based semantic approach to recognizing textual entailment
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Semantic inference at the lexical-syntactic level
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
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
What do we know about conversation participants: experiments on conversation entailment
SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Highlighting disputed claims on the web
Proceedings of the 19th international conference on World wide web
Towards conversation entailment: an empirical investigation
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Semi-supervised semantic role labeling via structural alignment
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
Automatic answer validation using COGEX
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
| Hi-index | 0.00 |
Semantic entailment is the problem of determining if the meaning of a given sentence entails that of another. This is a fundamental problem in natural language understanding that provides a broad framework for studying language variability and has a large number of applications. This paper presents a principled approach to this problem that builds on inducing representations of text snippets into a hierarchical knowledge representation along with a sound optimization-based inferential mechanism that makes use of it to decide semantic entailment. A preliminary evaluation on the PASCAL text collection is presented.