Mitigating linked data quality issues in knowledge-intense information extraction methods
Albert Weichselbraun, Philipp Kuntschik · 2017
Advances in research areas such as named entity linking and sentiment analysis have triggered the emergence of knowledge-intensive information extraction methods that combine classical information extraction with background knowledge from the Web. Despite data quality concerns, linked data sources such as DBpedia, GeoNames and Wikidata which encode facts in a standardized structured format are particularly attractive for such applications.