Robust tree-structured named entities recognition from speech
Résumé
Named Entity Recognition (NER) is a well-known Natural Language Processing (NLP) task, used as a preliminary processing to provide a semantic level to more complex tasks. Recently a new set of named entities has been defined, this set has a multilevel tree structure, where base entities are combined to define more complex ones. In this paper I describe, an effective and original NER system robust to noisy speech inputs that ranked first at the 2012 ETAP NER evaluation campaign with results far better than those of the other participating systems.
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