Publication | Closed Access
Performance issues and error analysis in an open-domain question answering system
234
Citations
23
References
2003
Year
EngineeringCorpus LinguisticsText MiningNatural Language ProcessingPerformance IssuesInformation RetrievalData ScienceComputational LinguisticsLanguage EngineeringLogic ProverSerial Baseline SystemLanguage StudiesIn-depth AnalysisMachine TranslationQuestion AnsweringNatural Language InterfaceNlp TaskOpen-domain QuestionComputer ScienceSemantic ParsingRetrieval Augmented GenerationError AnalysisAutomated ReasoningLinguistics
This paper presents an in-depth analysis of a state-of-the-art Question Answering system. Several scenarios are examined: (1) the performance of each module in a serial baseline system, (2) the impact of feedbacks and the insertion of a logic prover, and (3) the impact of various retrieval strategies and lexical resources. The main conclusion is that the overall performance depends on the depth of natural language processing resources and the tools used for answer finding.
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