Abstract
The task of disambiguation is to determine which of the senses of an ambiguous word is invoked in a particular use of the word [5],[8]. It is known that the statistical methods produce high accuracy results for semantically tagged corpora [2]. Also, Word Net is a good source of information for WSD [3],[4]. Since for Romanian language does not exist neither a corpus nor something similar with WordNet, we propose an algorithm for WSD which requires only information that can be extracted from untagged corpus. Our algorithm preserves the advantage of principles of Yarowsky [9],[7],[10] and adds the known high performance of a NBC algorithms. It learns to make predictions based on local context with only a few labeled contexts and many unlabeled ones.
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Şerban, G., TĂtar, D. (2003). Word Sense Disambiguation for Untagged Corpus: Application to Romanian Language. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2003. Lecture Notes in Computer Science, vol 2588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36456-0_26
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DOI: https://doi.org/10.1007/3-540-36456-0_26
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