Introduction to the CoNLL-2003 shared task: language-independent named entity recognition
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Learning to link entities with knowledge base
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Entity disambiguation for knowledge base population
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Entity linking leveraging: automatically generated annotation
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
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We present a joint system for named entity recognition (NER) and entity linking (EL), allowing for named entities mentions extracted from textual data to be matched to uniquely identifiable entities. Our approach relies on combined NER modules which transfer the disambiguation step to the EL component, where referential knowledge about entities can be used to select a correct entity reading. Hybridation is a main feature of our system, as we have performed experiments combining two types of NER, based respectively on symbolic and statistical techniques. Furthermore, the statistical EL module relies on entity knowledge acquired over a large news corpus using a simple rule-base disambiguation tool. An implementation of our system is described, along with experiments and evaluation results on French news wires. Linking accuracy reaches up to 87%, and the NER F-score up to 83%.