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- W2890754459 abstract "In this paper we present QA3, a question answering (QA) system over RDF data cubes. The system first tags chunks of text with elements of the knowledge base, and then leverages the well-defined structure of data cubes to create a SPARQL query from the tags. For each class of questions with the same structure a SPARQL template is defined, to be filled in with SPARQL fragments obtained by the interpretation of the question. The correct template is chosen by using an original set of regex-like patterns, based on both syntactical and semantic features of the tokens extracted from the question. Preliminary results obtained using a limited set of templates are encouraging and suggest a number of improvements. QA3 can currently provide a correct answer to 27 of the 50 questions of the test set of the task 3 of QALD-6 challenge, remarkably improving the state of the art in natural language question answering over data cubes." @default.
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- W2890754459 date "2019-04-05" @default.
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- W2890754459 title "QA 3 : A natural language approach to question answering over RDF data cubes" @default.
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- W2890754459 doi "https://doi.org/10.3233/sw-180328" @default.
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