WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
Automatic committed belief tagging
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Mining personal experiences and opinions from Web documents
Web Intelligence and Agent Systems
Are you sure that this happened? assessing the factuality degree of events in text
Computational Linguistics
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Recognizing textual entailment (TE) is a complex task involving knowledge from many different sources. One major source of information in this task is event factuality, since the inferences derivable from factual eventualities are different from those judged as possible or as non-existent. Some TE systems already factor in factuality features at the local level, but determining the factuality of events more generally involves dealing with information that is nonlocal to a particular textual event. In this paper, we present a tool providing events with their factuality values, characterized as pairs of modality and polarity features. In previous work, we identified polarity and modality at the local context with a performance of 92% precision and 56% recall. The research presented here extends and enhances our algorithm to incorporate the influence of non-local context as well as the identification of sources.