Publication | Closed Access
Textual evidence gathering and analysis
49
Citations
35
References
2012
Year
EngineeringDigital EvidenceCorpus LinguisticsJournalismText MiningApplied LinguisticsNatural Language ProcessingCandidate AnswerInformation RetrievalData ScienceDocument AnalysisComputational LinguisticsTextual Evidence GatheringRelevance FeedbackDiscourse AnalysisLanguage StudiesContent AnalysisMachine TranslationQuestion AnsweringKnowledge RetrievalKnowledge DiscoveryComputer ScienceEvidence-based RecommendationReasoningRetrieval Augmented GenerationDeepqa PipelineAutomated ReasoningEvidence RetrievalLinguisticsInteractive Information Retrieval
One useful source of evidence for evaluating a candidate answer to a question is a passage that contains the candidate answer and is relevant to the question. In the DeepQA pipeline, we retrieve passages using a novel technique that we call Supporting Evidence Retrieval, in which we perform separate search queries for each candidate answer, in parallel, and include the candidate answer as part of the query. We then score these passages using an assortment of algorithms that use different aspects and relationships of the terms in the question and passage. We provide evidence that our mechanisms for obtaining and scoring passages have a substantial impact on the ability of our question-answering system to answer questions and judge the confidence of the answers.
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