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%.
