WSDGate is a supervised Target-Word Sense Disambiguation (WSD) toolkit for GATE and combines the functionality of GATE, NSPGate and WEKA to provide an end-to-end solution for target-word WSDby combining feature identification and extraction using GATE and modified versions of its plugins and supervised machine learning using WEKA.
Here's the project page for WSDGate. The latest version is version 0.05, which can be downloaded from this project page link.
The README, USAGE and INSTALL documentation is available.
The following are publications about WSDGate or using experiments performed with the help of WSDGate:
Mahesh Joshi, Serguei Pakhomov, Ted Pedersen, Richard Maclin, and Christopher Chute. An End-to-End Supervised Target-Word Sense Disambiguation System. Appears in Proceedings of the Twenty-first National Conference on Artificial Intelligence (AAAI-06), Intelligent Systems Demonstrations. July 2006, Boston, MA. pp. 1941--1942. download pdf
Mahesh Joshi, Serguei Pakhomov, Ted Pedersen, and Christopher Chute. A Comparative Study of Supervised Learning as Applied to Acronym Expansion in Clinical Reports. To appear in Proceedings of the American Medical Informatics Association Annual Symposium (AMIA-06). download pdf