Learning Effective Surface Text Patterns for Information Extraction
Gijs Geleijnse, Jan Korst · 2006
We present a novel method to identify effective surface text patterns using an internet search engine. Precision is only one of the criteria to identify the most effective patterns among the candidates found. Another aspect is frequency of occurrence. Also, a pattern has to relate diverse instances if it expresses a non-functional relation. The learned surface text patterns are applied in an ontology population algorithm, which not only learns new instances of classes but also new instancepairs of relations. We present some £rst experiments with these methods.