Recognizing Textual Entailment with Tree Edit Distance: Application to Question Answering and Information Extraction

This thesis addresses the problem of Recognizing Textual Entailment (i.e. recognizing that the meaning of a text entails the meaning of another text) using a Tree Edit Distance algorithm between the syntactic trees of the two texts. A key aspect of the approach is the estimation of the cost for the editing operations (i.e. Insertion, Deletion, Substitution) among words. Our aim is to compare the contribution of different resources providing entailment rules, including lexical rules from WordNet and the UniAlberta thesaurus, and syntactic rules automatically acquired by the Dirt and TEASE systems. We carried out a number of experiments over the PASCAL-RTE dataset in order to estimate the contribution of different combinations of the available resources. In addition, we have developed and evaluated an Answer Validation module for Question Answering and a Relation Extraction system, both of them based on textual entailment.