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Language-Agnostic Relation Extraction from Abstracts in Wikis
2018
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Large-scale knowledge graphs, such as DBpedia, Wikidata, or YAGO, can be enhanced by relation extraction from text, using the data in the knowledge graph as training data, i.e., using distant supervision. While most existing approaches use language-specific methods (usually for English), we present a language-agnostic approach that exploits background knowledge from the graph instead of language-specific techniques and builds machine learning models only from language-independent features. We
doi:10.3390/info9040075
fatcat:juilvyj47bgclpax63dv4wimw4