Learning Relations using Collocations

2nd Workshop on Ontology Learning OL'2001

计算机科学;社会科学（总论）

Gerhard Heyer ; Martin Läuter ; Uwe Quasthoff ; Thomas Wittig ; Christian Wolff

PID  :  79998

来源: CEUR

【 摘 要 】

This paper describes the application of statistical analysis of large corpora to the problem of extracting semantic relations from unstructured text. We regard this approach as a viable method for generating input for the construction of ontologies as ontologies use welldefined semantic relations as building blocks (cf. van der Vet & Mars 1998). Starting from a short description of our corpora as well as our language analysis tools, we discuss in depth the automatic generation of collocation sets. We further give examples of different types of relations that may be found in collocation sets for arbitrary terms. The central question we deal with here is how to postprocess statistically generated collocation sets in order to extract named relations. We show that for different types of relations like cohyponyms or instanceofrelations, different extraction methods as well as additional sources of information can be applied to the basic collocation sets in order to verify the existence of a specific type