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Title: Disambiguation of human names in text
Authors: Shanaz, A. L. F.
Ragel, R.
Keywords: Named entity linking
Named entity disambiguation
Issue Date: 2018
Publisher: South Eastern University of Sri Lanka, University Park, Oluvil, Sri Lanka.
Citation: 8th International Symposium 2018 on “Innovative Multidisciplinary Research for Green Development”. 17th - 18th December, 2018. South Eastern University of Sri Lanka, University Park, Oluvil, Sri Lanka. pp. 205-225.
Abstract: The aim of this paper is to implement an entity linking system for news recommendation. Which can automatically recognize Person entities (humans) from input English text (news article), and link them to the best-matched entities in Wikidata knowledge base. That is, for each specific mention of a person entity found in a text, the developed Named Entity Disambiguation (NED) algorithm was applied to search for candidate entities (in Wikidata) and return either the best candidate or a NIL reference if the spotted person entity does not match any Human in Wikidata. In a nutshell, our system maps mentions of ambiguous human names (people mention) in text onto Wikidata unique identifier (Q number). We extensively evaluated the performance of our system over manually annotated AIDA CoNLL-YAGO Dataset, and the experimental results show that our system achieves the top-5 precision of 84.4%.
ISBN: 978-955-627-141-6
Appears in Collections:8th International Symposium - 2018

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