Building a Graph of Names and Contextual Patterns for Named Entity Classification

Authors:
César Pablo-Sánchez;Paloma Martínez
Affiliations:
Computer Science Department, Universidad Carlos III de Madrid, Leganés, Spain 28911;Computer Science Department, Universidad Carlos III de Madrid, Leganés, Spain 28911
Venue:
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Year:
2009

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Abstract

An algorithm that bootstraps the acquisition of large dictionaries of entity types (names) and pattern types from a few seeds and a large unannotated corpora is presented. The algorithm iteratively builds a bigraph of entities and collocated patterns by querying the text. Several classes simultaneously compete to label the entity types. Different experiments have been carried to acquire resources from a 1GB corpus of Spanish news. The usefulness of the acquired list of entity types for the task of Name Classification has also been evaluated with good results for a weakly supervised method.