A Weakly-Supervised Rule-Based Approach for Relation Extraction

TítuloA Weakly-Supervised Rule-Based Approach for Relation Extraction
AutoresGarcia, Marcos and Pablo Gamallo
TipoComunicación para congreso
Fonte XIV Conference of the Spanish Association for Artificial Intelligence, San Cristobal de la Laguna, Spain, 2011.
AbstractRule-based approaches for information extraction usually achieve good precision values, even if they often need a lot of manual e ort to be implemented. In this paper, we present a novel rule-based strategy for semantic relation extraction that takes advantage of partial syntactic parsing in order to simplify the linguistic structures containing instances of semantic relations. We also propose a distant supervision strategy that automatically extracts generic lexico-syntactic patterns by means of semi-structured resources such as Wikipedia infoboxes. These generic patterns are then transformed into extraction rules that are used to update a partial dependency grammar. Several evaluations of this method show that it improves the recall while maintaining high-precision values. Experiments were performed on Spanish texts.
Palabras chaveinformation extraction, relation extraction, ontologies, lexico-syntactic patterns, text compression