  The goal of this work is to improve the performance of a neural named entity
recognition system by adding input features that indicate a word is part of a
name included in a gazetteer. This article describes how to generate gazetteers
from the Wikidata knowledge graph as well as how to integrate the information
into a neural NER system. Experiments reveal that the approach yields
performance gains in two distinct languages: a high-resource, word-based
language, English and a high-resource, character-based language, Chinese.
Experiments were also performed in a low-resource language, Russian on a newly
annotated Russian NER corpus from Reddit tagged with four core types and twelve
extended types. This article reports a baseline score. It is a longer version
of a paper in the 33rd FLAIRS conference (Song et al. 2020).
