Logical foundations of artificial intelligence
Logical foundations of artificial intelligence
Artificial Intelligence - Special volume on natural language processing
WordNet: a lexical database for English
Communications of the ACM
Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
Experiments with open-domain textual Question Answering
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
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
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
WordNet: similarity - measuring the relatedness of concepts
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Robust textual inference via graph matching
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Recognising textual entailment with logical inference
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
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
Measures of semantic similarity and relatedness in the biomedical domain
Journal of Biomedical Informatics
Identifying semantic equivalence for multi-document summarisation
Artificial Intelligence Review
Scaling textual inference to the web
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Semantic inference at the lexical-syntactic level
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Learning alignments and leveraging natural logic
RTE '07 Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing
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
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
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
Towards a framework for developing semantic relatedness reference standards
Journal of Biomedical Informatics
An inference model for semantic entailment in natural language
MLCW'05 Proceedings of the First international conference on Machine Learning Challenges: evaluating Predictive Uncertainty Visual Object Classification, and Recognizing Textual Entailment
Textual entailment recognition using a linguistically–motivated decision tree classifier
MLCW'05 Proceedings of the First international conference on Machine Learning Challenges: evaluating Predictive Uncertainty Visual Object Classification, and Recognizing Textual Entailment
Recognising textual entailment with robust logical inference
MLCW'05 Proceedings of the First international conference on Machine Learning Challenges: evaluating Predictive Uncertainty Visual Object Classification, and Recognizing Textual Entailment
Learning entailment relations by global graph structure optimization
Computational Linguistics
A probabilistic lexical model for ranking textual inferences
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
JELIA'12 Proceedings of the 13th European conference on Logics in Artificial Intelligence
Learning to predict from textual data
Journal of Artificial Intelligence Research
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We present a system for textual inference (the task of inferring whether a sentence follows from another text) that uses learning and a logical-formula semantic representation of the text. More precisely, our system begins by parsing and then transforming sentences into a logical formula-like representation similar to the one used by (Harabagiu et al., 2000). An abductive theorem prover then tries to find the minimum "cost" set of assumptions necessary to show that one statement follows from the other. These costs reflect how likely different assumptions are, and are learned automatically using information from syntactic/semantic features and from linguistic resources such as WordNet. If one sentence follows from the other given only highly plausible, low cost assumptions, then we conclude that it can be inferred. Our approach can be viewed as combining statistical machine learning and classical logical reasoning, in the hope of marrying the robustness and scalability of learning with the preciseness and elegance of logical theorem proving. We give experimental results from the recent PASCAL RTE 2005 challenge competition on recognizing textual inferences, where a system using this inference algorithm achieved the highest confidence weighted score.