Towards a theory of natural language interfaces to databases
Proceedings of the 8th international conference on Intelligent user interfaces
Methods for using textual entailment in open-domain question answering
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the 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
Overview of the answer validation exercise 2006
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
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
Dealing with Spoken Requests in a Multimodal Question Answering System
AIMSA '08 Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications
Towards Extensible Textual Entailment Engines: The EDITS Package
AI*IA '09: Proceedings of the XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia on Emergent Perspectives in Artificial Intelligence
QALL-ME needs AIR: a portability study
AdaptLRTtoND '09 Proceedings of the Workshop on Adaptation of Language Resources and Technology to New Domains
Selecting Answers to Questions from Web Documents by a Robust Validation Process
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
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This paper presents a novel approach to Question Answering over structured data, which is based on Textual Entailment recognition. The main idea is that the QA problem can be recast as an entailment problem, where the text (T) is the question and the hypothesis (H) is a relational pattern, which is associated to "instructions" for retrieving the answer to the question. In this framework, given a question Q and a set of answer patterns P, the basic operation is to select those patterns in P that are entailed by Q. We report on a number of experiments which show the great potentialities of the proposed approach.