FRDC's Cross-lingual Entity Linking System at TAC 2013

Qingliang Miao, Ruiyu Fang, Yao Meng, Shu Zhang
2013 Text Analysis Conference  
In this paper, we present FRDC's system at participating in the cross-lingual entity linking (CLEL) tasks for the NIST Text Analysis Conference (TAC) Knowledge Base Population (KBP2013) track. We propose a joint approach for mention expansion, disambiguation, and clustering. In particular, we adopt a lexicon and rule based method for entity classification, a collaborative acronym expansion method and a heuristic combination ranking method that merged ListNet, SVM ranking with web search engine
more » ... anking. The results achieved in the TAC cross-lingual entity linking tasks show that our approach is competitive. Our best run achieves 0.655 in B^3+ F1 measure.
dblp:conf/tac/MiaoFMZ13 fatcat:77rrw626t5gs5jqij72bziawdi