Textual Entailment Using Univariate Density Model and Maximizing Discriminant Function

The primary focuses of this entry this year was firstly, to develop a framework to allow multiple researchers from our group to easily contribute metrics measuring textual entailment, and secondly, to provide a baseline which we could use in our tools to evaluate and compare new metrics. A development environment tool was created to quickly allow for testing of various metrics and to easily randomize the development and test sets. For each test, this RTE tool calculated two sets of results by applying the metrics to both a univariate Gaussian density and by maximizing a linear discriminant function. The metrics used for the submission were a lexical similarity metric and a lexical similarity metric using synonym and antonym replacement. The two submissions for RTE 2007 scored an accuracy of 61.00% and 62.62%.