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HeadlineStanceChecker: Exploiting summarization to detect headline disinformation
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Cross-document event ordering through temporal, lexical and distributional knowledge
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LEGOLANG: técnicas de deconstrucción aplicadas a las tecnologías del lenguaje humano ; LEGOLANG: deconstruction techniques applied to human language technologies
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A semantic approach to temporal information processing ; Una aproximació semàntica al processament de la informació temporal
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Enhancing QA systems with complex temporal question processing capabilities
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Detección de expresiones temporales TimeML en catalán mediante roles semánticos y redes semánticas ; TimeML temporal expressions detection for Catalan using semantic roles and semantic networks
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The influence of semantic roles in QA: a comparative analysis ; La influencia de los roles semanticos en BR: un análisis comparativo
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Multilingual extension of temporal expression recognition using parallel corpora
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Evaluating knowledge-based approaches to the multilingual extension of a temporal expression normalizer
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Multilingual extension of a temporal expression normalizer using annotated corpora
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Splitting complex temporal questions for question answering systems
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Abstract:
This paper presents a multi-layered Question Answering (Q.A.) architecture suitable for enhancing current Q.A. capabilities with the possibility of processing complex questions. That is, questions whose answer needs to be gathered from pieces of factual information scattered in different documents. Specifically, we have designed a layer oriented to process the different types of temporal questions. Complex temporal questions are first decomposed into simpler ones, according to the temporal relationships expressed in the original question. In the same way, the answers of each simple question are re-composed, fulfilling the temporal restrictions of the original complex question. Using this architecture, a Temporal Q.A. system has been developed. In this paper, we focus on explaining the first part of the process: the decomposition of the complex questions. Furthermore, it has been evaluated with the TERQAS question corpus of 112 temporal questions. For the task of question splitting our system has performed, in terms of precision and recall, 85% and 71%, respectively. ; This paper has been supported by the Spanish government, projects FIT-150500-2002-244, FIT-150500-2002-416, TIC-2003-07158-C04-01 and TIC2000-0664-C02-02.
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Keyword:
Complex temporal questions; Lenguajes y Sistemas Informáticos; Multi-layered QA system architecture; Question answering
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URL: http://hdl.handle.net/10045/22532
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Grammar specification for the recognition of temporal expressions
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