Increasing availability of on-line and off-line multilingual resources along with the developments in the related automatic tools that can process this information, such as GIZA++ (Och & Ney 2003), has made it possible to build new multilingual resources that can be used for NLP/IR tasks. Lexicon generation is one such task, which if done by hand is quite expensive with human and capital costs involved. Generation of multilingual lexicons can now be automated, as is done in this research work. Wikipedia, an on-line multilingual resource was gainfully employed to automatically build multilingual lexicons using simple search strategies. Europarl parallel corpus (Koehn 2002) was used to create multilingual sets of synonyms, that were later used to carry out the task of Word Sense Disambiguation (WSD) on the original corpus from which they were derived. The theoretical analysis of the methodology validated our approach. The multilingual sets of synonyms were then used to learn unsupervised models of word morphology in the individual languages. The set of experiments we carried out, along with another unsupervised technique, were evaluated against the gold standard. Our results compared very favorably with the other approach. The combination of the two approaches gave even better results.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:550283 |
| Date | January 2012 |
| Creators | Shahid, Ahmad |
| Contributors | Kazakov, Dimitar |
| Publisher | University of York |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://etheses.whiterose.ac.uk/2111/ |
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