Name: wikiann
Description:  Both name tagging and linking results for 282 languages are promising on Wikipedia data and on-Wikipedia
  data
Provider: Multiple institutions
Paper Title: Cross-lingual Name Tagging and Linking for 282 Languages
  
Tasks: named entity recognition
Venue Name: Assofications of computation linguisitcs
Authors: Xiaoman Pan,Boliang Zhang,Jonathan May,J. Nothman,Kevin Knight,Heng Ji
Abstract: The ambitious goal of this work is to develop a cross-lingual name tagging and linking framework for 282 languages that exist in Wikipedia. Given a document in any of these languages, our framework is able to identify name mentions, assign a coarse-grained or fine-grained type to each mention, and link it to an English Knowledge Base (KB) if it is linkable. We achieve this goal by performing a series of new KB mining methods: generating “silver-standard” annotations by transferring annotations from English to other languages through cross-lingual links and KB properties, refining annotations through self-training and topic selection, deriving language-specific morphology features from anchor links, and mining word translation pairs from cross-lingual links. Both name tagging and linking results for 282 languages are promising on Wikipedia data and on-Wikipedia data.