Named Entity Recognition based on a Graph Structure

David Muñoz, Fernando Pérez, David Pinto


The identication of indirect relationships between texts from diferent sources makes the task of text mining useful when the goal is to obtain the most valuable information from a set of texts. That is why in the eld of information retrieval the correct recognition of named entities plays an important role when extracting valuable information in large amounts of text. Therefore, it is important to propose techniques that improve the NER classiers in order to achieve the correct recognition of named entities. In this work, a graph structure for storage and enrichment of named entities is proposed. It makes use of synonyms and domain-specic ontologies in the area of computing. The performance of the proposed structure is measured and compared with other NER classiers in the experiments carried out.


NER, N-grams, text representation, graph-based representation, named entity recognition

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