Unsupervised Resource Creation for Textual Inference Applications

This paper explores how a battery of unsupervised techniques can be used in order to create large, high-quality corpora for textual inference applications, such as systems for recognizing textual entailment (TE) and textual contradiction (TC). We show that it is possible to automatically generate sets of positive and negative instances of textual entailment and contradiction from textual corpora with greater than 90% precision. We describe how we generated more than 1 million TE pairs

• Type: Conference
• Year: 2008
• Where: LREC
• Authors: Jeremy Bensley, Andrew Hickl
• Keywords: Education, LREC 2008, Textual, Textual Entailment, Textual Inference Applications