Resolving Part-of-Speech Ambiguity in the Greek Language Using Learning Techniques
<|reference_start|>Resolving Part-of-Speech Ambiguity in the Greek Language Using Learning Techniques: This article investigates the use of Transformation-Based Error-Driven learning for resolving part-of-speech ambiguity in the Greek language. The aim is not only to study the performance, but also to examine its dependence on different thematic domains. Results are presented here for two different test cases: a corpus on "management succession events" and a general-theme corpus. The two experiments show that the performance of this method does not depend on the thematic domain of the corpus, and its accuracy for the Greek language is around 95%.<|reference_end|>
@article{petasis1999resolving,
    title={Resolving Part-of-Speech Ambiguity in the Greek Language Using Learning
  Techniques},
    author={G. Petasis, G. Paliouras, V. Karkaletsis, C. D. Spyropoulos and I.
  Androutsopoulos (Software & Knowledge Engineering Lab, Institute of
  Informatics & Telecommunications, NCSR Demokritos, Greece)},
    journal={In Fakotakis, N. et al. (Eds.), Machine Learning in Human Language
  Technology (Proceedings of the ACAI Workshop), pp. 29-34, Chania, Greece,
  1999.},
    year={1999},
    archivePrefix={arXiv},
    eprint={cs/9906019},
    primaryClass={cs.CL cs.AI}
}