Textual entailment through extended lexical overlap and lexico-semantic matching
Rod Adams, Gabriel Nicolae, Cristina Nicolae, Sanda M. Harabagiu · 2007
This paper presents two systems for textual entailment, both employing decision trees as a supervised learning algorithm. The first one is based primarily on the concept of lexical overlap, considering a bag of words similarity overlap measure to form a mapping of terms in the hypothesis to the source text. The second system is a lexico-semantic matching between the text and the hypothesis that attempts an alignment between chunks in the hypothesis and chunks in the text, and a representation of the text and hypothesis as two dependency graphs. Their performances are compared and their positive and negative aspects are analyzed.