Publication | Open Access
Using syntactic information for improving<i>why</i>-question answering
30
Citations
8
References
2008
Year
Unknown Venue
Syntactic ParsingEngineeringIntelligent Information RetrievalWhy-question AnsweringQuestion FocusSyntactic StructureCorpus LinguisticsText MiningNatural Language ProcessingSyntaxInformation RetrievalComputational LinguisticsRelevance FeedbackLanguage StudiesMachine TranslationQuestion AnsweringRetrieval Augmented GenerationAutomated ReasoningParagraph Retrieval ApproachSyntactic InformationLinguisticsInteractive Information Retrieval
In this paper, we extend an existing paragraph retrieval approach to why-question answering. The starting-point is a system that retrieves a relevant answer for 73% of the test questions. However, in 41% of these cases, the highest ranked relevant answer is not ranked in the top-10. We aim to improve the ranking by adding a re-ranking module. For re-ranking we consider 31 features pertaining to the syntactic structure of the question and the candidate answer. We find a significant improvement over the baseline for both [email protected] and [email protected] The most important features for re-ranking are the baseline score, the presence of cue words, the question's main verb, and the relation between question focus and document title.
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