Publication | Open Access
QAnswer: A Question Answering prototype bridging the gap between a considerable part of the LOD cloud and end-users
33
Citations
8
References
2019
Year
Unknown Venue
ChatbotEngineeringSemantic SearchIntelligent Information RetrievalQuery ModelQuestion Answering SystemSemantic WebText MiningNatural Language ProcessingInformation RetrievalData ScienceConsiderable PartComputational LinguisticsData IntegrationData ManagementQuestion AnsweringNatural Language InterfaceComputer ScienceQuestion Answering PrototypeRetrieval Augmented GenerationLod CloudHuman-computer InteractionTechnology
We present QAnswer, a Question Answering system which queries at the same time 3 core datasets of the Semantic Web, that are relevant for end-users. These datasets are Wikidata with Lexemes, LinkedGeodata and Musicbrainz. Additionally, it is possible to query these datasets in English, German, French, Italian, Spanish, Pourtuguese, Arabic and Chinese. Moreover, QAnswer includes a fallback option to the search engine Qwant when the answer to a question cannot be found in the datasets mentioned above. These features make QAnswer as the first prototype of a Question Answering System over a considerable part of the LOD cloud.
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