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Capturing knowledge in semantically-typed relational patterns to enhance relation linking
Conference ObjectAbstract: Transforming natural language questions into formal queries is an integral task in Question AnswerinPalabras claves:Knowledge Capture, Knowledge graphs, Question Answering Systems, relation linkingAutores:Auer S., Jaradeh M.Y., Lange C., Lytra I., María-Esther Vidal, Mulang’ I.O., Sakor A., Singh K.Fuentes:scopusFalCon: An entity and relation linking framework over dbpedia
Conference ObjectAbstract: We tackle the problem of entity and relation linking and present FALCON, a rule-based tool able to aPalabras claves:Background Knowledge, English morphology, entity linking, NLP, relation linkingAutores:María-Esther Vidal, Sakor A., Singh K.Fuentes:scopusFalcon 2.0: An Entity and Relation Linking Tool over Wikidata
Conference ObjectAbstract: The Natural Language Processing (NLP) community has significantly contributed to the solutions for ePalabras claves:Background Knowledge, dbpedia, English morphology, entity linking, NLP, relation linking, WikidataAutores:María-Esther Vidal, Patel A., Sakor A., Singh K.Fuentes:scopusEncoding Knowledge Graph Entity Aliases in Attentive Neural Network for Wikidata Entity Linking
Conference ObjectAbstract: The collaborative knowledge graphs such as Wikidata excessively rely on the crowd to author the infoPalabras claves:entity linking, Knowledge graph context, WikidataAutores:Auer S., María-Esther Vidal, Mulang’ I.O., Shekarpour S., Singh K., Vyas A.Fuentes:scopusDynamic composition of question answering pipelines with Frankenstein
Conference ObjectAbstract: Question answering (QA) systems provide user-friendly interfaces for retrieving answers from structuPalabras claves:QA framework, Question answering, semantic search, semantic web, Software ReusabilityAutores:Lytra I., María-Esther Vidal, Radhakrishna A.S., Singh K., Vyas A.Fuentes:scopusNo one is perfect: Analysing the performance of question answering components over the DBpedia knowledge graph
ArticleAbstract: Question answering (QA) over knowledge graphs has gained significant momentum over the past five yeaPalabras claves:entity linking, Experiment and analysis, Knowledge Graph, Question answering, Relation extraction, relation linkingAutores:Lehmann J., Lytra I., María-Esther Vidal, Radhakrishna A.S., Shekarpour S., Singh K.Fuentes:scopusOld is gold: Linguistic driven approach for entity and relation linking of short text
Conference ObjectAbstract: Short texts challenge NLP tasks such as named entity recognition, disambiguation, linking and relatiPalabras claves:Autores:Auer S., Lehmann J., María-Esther Vidal, Mulang’ I.O., Sakor A., Shekarpour S., Singh K.Fuentes:scopusWhy reinvent the wheel: Let's build question answering systems together
Conference ObjectAbstract: Modern question answering (QA) systems need to flexibly integrate a number of components specialisedPalabras claves:QA framework, Question answering, semantic search, semantic web, Software ReusabilityAutores:Auer S., Both A., Khikmatullaev A., Lange C., Lehmann J., Lytra I., María-Esther Vidal, Punjani D., Radhakrishna A.S., Shekarpour S., Singh K., Usbeck R., Vyas A.Fuentes:scopusQAESTRO framework - Semantic composition of QA pipelines
Conference ObjectAbstract: Many question answering systems and related components have been developed in recent years. Since quPalabras claves:Question answering, SAT solver, Software ReusabilityAutores:Aditya K., Lytra I., María-Esther Vidal, Singh K.Fuentes:scopusQAestro – Semantic-based composition of question answering pipelines
Conference ObjectAbstract: The demand for interfaces that allow users to interact with computers in an intuitive, effective, anPalabras claves:Autores:Auer S., Lange C., Lytra I., María-Esther Vidal, Punjani D., Singh K., Thakkar H.Fuentes:scopus