Automatic Extraction of Examples for Word Sense Disambiguation

Master's Thesis from the year 2009 in the subject Communications - Language, grade: 1.3, University of Tubingen (Seminar fr Sprachwissenschaft), course: Computerlinguistik, language: English, abstract: In the following thesis we present a memory-based word sense disambiguation system, which makes use of automatic feature selection and minimal parameter optimization. We show that the system performs competitive to other state-of-art systems and use it further for evaluation of automatically acquired data for word sense disambiguation.
The goal of the thesis is to demonstrate that automatically extracted examples for word sense disambiguation can help increase the performance of supervised approaches. We conducted several experiments and discussed their results in order to illustrate the advantages and disadvantages of the automatically acquired data.