Learning Semantic-Level Information Extraction Rules by Type-Oriented ILP

This paper describes an approach to using semantic rcprcsentations for learning information extraction (IE) rules by a type-oriented inductire logic programming (ILl)) system. NLP components of a lnachine translation system are used to automatically generate semantic representations of text corpus that can be given directly to an ILP system. The latest experimental results show high precision and recall of the learned rules.

• Type: Conference
• Year: 2000
• Where: COLING
• Authors: Yutaka Sasaki, Yoshihiro Matsuo
• Keywords: COLING 2000, COLING 2008, Inductire Logic Programming, Semantic Rcprcsentations, Semantic Representations