Alan Akbik, Alexander Löser:
KrakeN: N-Ary Facts in Open Information Extraction
In: The Knowledge Extraction Workshop at NAACL-HLT, 2012 (7-8 June 2012, Montréal, Canada)
Abstract
Current techniques for Open Information Extraction (OIE) focus on the extraction of binary facts and suffer significant quality loss for the task of extracting higher order N-ary facts. This quality loss may not only affect the correctness, but also the completeness of an extracted fact. We present KrakeN, an OIE system specifically designed to capture N-ary facts, as well as the results of an experimental study on extracting facts from Web text in which we examine the issue of fact completeness. Our preliminary experiments indicate that KrakeN is a high precision OIE approach that captures more facts per sentence at greater completeness than existing OIE approaches, but is vulnerable to noisy and ungrammatical text.
Download: link
