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Improving Multilingual Named Entity Recognition with Wikipedia Entity Type Mapping
2016
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing
The state-of-the-art named entity recognition (NER) systems are statistical machine learning models that have strong generalization capability (i.e., can recognize unseen entities that do not appear in training data) based on lexical and contextual information. However, such a model could still make mistakes if its features favor a wrong entity type. In this paper, we utilize Wikipedia as an open knowledge base to improve multilingual NER systems. Central to our approach is the construction of
doi:10.18653/v1/d16-1135
dblp:conf/emnlp/NiF16
fatcat:z2fyglnnsndhdd7brduzc5ozq4