AdArte

Introduction

AdArte (A Transformation-Driven Approach for Recognizing Textual Entailment) is based on modelling entailment relations as a classification problem where the single T-H pairs are first represented by a sequence of edit operations (i.e., deleting, replacing and inserting pieces of text) called transformations needed to transform T into H, and then used as features to feed up a supervised learning classifier to classify the pairs as positive or negative examples.

A complete documentation of AdArte EDA will be available in days.

Known Bugs and Limitations:

• Some dependencies version in the adarte project file are wrong (1.2.0 instead of 1.2.1) and have to substituted with the following ones:

<dependency>
  <groupId>eu.excitementproject</groupId>
  <artifactId>common</artifactId>
  <version>1.2.1</version>
</dependency>
<dependency>
  <groupId>eu.excitementproject</groupId>
  <artifactId>lap</artifactId>
  <version>1.2.1</version>
</dependency>
<dependency>
  <groupId>eu.excitementproject</groupId>
  <artifactId>distsim</artifactId>
  <version>1.2.1</version>
</dependency>
<dependency>
  <groupId>eu.excitementproject</groupId>
  <artifactId>core</artifactId>
  <version>1.2.1</version>
</dependency>