acl acl2010 acl2010-30 acl2010-30-reference knowledge-graph by maker-knowledge-mining

30 acl-2010-An Open-Source Package for Recognizing Textual Entailment


Source: pdf

Author: Milen Kouylekov ; Matteo Negri

Abstract: This paper presents a general-purpose open source package for recognizing Textual Entailment. The system implements a collection of algorithms, providing a configurable framework to quickly set up a working environment to experiment with the RTE task. Fast prototyping of new solutions is also allowed by the possibility to extend its modular architecture. We present the tool as a useful resource to approach the Textual Entailment problem, as an instrument for didactic purposes, and as an opportunity to create a collaborative environment to promote research in the field.


reference text

Prodromos Malakasiotis and Ion Androutsopoulos 2007. Learning Textual Entailment using SVMs and String Similarity Measures. Proc. of the ACL ’07 Workshop on Textual Entailment and Paraphrasing. Ido Dagan and 0ren Glickman 2004. Probabilistic Textual Entailment: Generic Applied Modeling of Language Variability. Proc. of the PASCAL Workshop on Learning Methods for Text Understanding and Mining. Kaizhong Zhang and Dennis Shasha 1990. Fast Algorithm for the Unit Cost Editing Distance Between Trees. Journal of Algorithms. vol.1 1. Yashar Mehdad 2009. Automatic Cost Estimation for Tree Edit Distance Using Particle Swarm Optimization. Proc. of ACL-IJCNLP 2009. Matteo Negri and Milen Kouylekov 2009. Question Answering over Structured Data: an EntailmentBased Approach to Question Analysis. Proc. of RANLP-2009. Elena Cabrio, Yashar Mehdad, Matteo Negri, Milen Kouylekov, and Bernardo Magnini 2009. Recognizing Textual Entailment for Italian EDITS @ EVALITA 2009 Proc. of EVALITA 2009. Yashar Mehdad, Matteo Negri, Elena Cabrio, Milen Kouylekov, and Bernardo Magnini 2009. Recognizing Textual Entailment for English EDITS @ TAC 2009 To appear in Proceedings of TAC 2009. 47