Preemptive information extraction using unrestricted relation discovery 论文

2006引用 242
Natural Language Processing TechniquesTopic ModelingSemantic Web and Ontologies

摘要

We are trying to extend the boundary of Information Extraction (IE) systems. Existing IE systems require a lot of time and human effort to tune for a new scenario. Preemptive Information Extraction is an attempt to automatically create all feasible IE systems in advance without human intervention. We propose a technique called Unrestricted Relation Discovery that discovers all possible relations from texts and presents them as tables. We present a preliminary system that obtains reasonably good results.