NLP Questions Answering Using DBpedia and YAGO
نویسندگان
چکیده
منابع مشابه
A Comparative Survey of DBpedia, Freebase, OpenCyc, Wikidata, and YAGO
In recent years, several noteworthy large, crossdomain and openly available knowledge graphs (KGs) have been created. These include DBpedia, Freebase, OpenCyc, Wikidata, and YAGO. Although extensively in use, these KGs have not been subject to an in-depth comparison so far. In this survey, we first define aspects according to which KGs can be analyzed. Next, we analyze and compare the above men...
متن کاملLinked data quality of DBpedia, Freebase, OpenCyc, Wikidata, and YAGO
In recent years, several noteworthy large, cross-domain, and openly available knowledge graphs (KGs) have been created. These include DBpedia, Freebase, OpenCyc, Wikidata, and YAGO. Although extensively in use, these KGs have not been subject to an in-depth comparison so far. In this survey, we provide data quality criteria according to which KGs can be analyzed and analyze and compare the abov...
متن کاملQuestion Answering Using a Large NLP System
The Microsoft Research question-answering system for TREC-9 was based on a combination of the Okapi retrieval engine, Microsoft’s natural language processing system (NLPWin), and a module for matching logical forms. There is no recent published account of NLPWin, although a description of its predecessor can be found in Jensen et al. (1993). NLPWin accepts sentences and delivers a detailed synt...
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Recently, the DBpedia community has experienced an immense increase in activity and we believe, that the time has come to explore the connection between DBpedia & Natural Language Processing (NLP) in a yet unprecedented depth. DBpedia has a long-standing tradition to provide useful data as well as a commitment to reliable Semantic Web technologies and living best practices. As the extraction of...
متن کاملTranslating Questions into Answers using DBPedia n-triples
In this paper we present a question answering system using a neural network to interpret questions learned from the DBpedia repository. We train a sequenceto-sequence neural network model with n-triples extracted from the DBpedia Infobox Properties. Since these properties do not represent the natural language, we further used question-answer dialogues from movie subtitles. Although the automati...
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ژورنال
عنوان ژورنال: Vietnam Journal of Computer Science
سال: 2020
ISSN: 2196-8888,2196-8896
DOI: 10.1142/s2196888820500190