SeMantic AnsweR Type prediction task (SMART) at ISWC 2020 Semantic Web Challenge

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Authors Nandana Mihindukulasooriya, Mohnish Dubey, Alfio Gliozzo, Jens Lehmann, Axel-Cyrille Ngonga Ngomo, Ricardo Usbeck arXiv ID 2012.00555 Category cs.AI: Artificial Intelligence Cross-listed cs.CL, cs.IR Citations 17 Venue arXiv.org Last Checked 4 months ago
Abstract
Each year the International Semantic Web Conference accepts a set of Semantic Web Challenges to establish competitions that will advance the state of the art solutions in any given problem domain. The SeMantic AnsweR Type prediction task (SMART) was part of ISWC 2020 challenges. Question type and answer type prediction can play a key role in knowledge base question answering systems providing insights that are helpful to generate correct queries or rank the answer candidates. More concretely, given a question in natural language, the task of SMART challenge is, to predict the answer type using a target ontology (e.g., DBpedia or Wikidata).
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