Abstract
In this paper we present the comparative research work disclosing strengths and weaknesses of two the most popular and publicly available Lithuanian morphological analyzers, in particular, Lemuoklis and Semantika.lt. Their lemmatization, part-of-speech tagging, and fined-grained annotation of the morphological categories (as case, gender, tense, etc.) performance was evaluated on the morphologically annotated gold standard corpus composed of four domains, in particular, administrative, fiction, scientific and periodical texts. Semantika.lt significantly outperformed Lemuoklis by \(\sim \)1.7%, \(\sim \)2.5%, and \(\sim \)8.1% on the lemmatization, part-of-speech tagging, and fine-grained annotation tasks achieving \(\sim \)98.0%, \(\sim \)95.3% and, \(\sim \)86.8% of the accuracy, respectively.
Semantika.lt was also superior on the administrative, fiction, and periodical texts; however, Lemuoklis yielded similar performance on the scientific texts and even bypassed Semantika.lt in the fine-grained annotation task.
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Notes
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More about the Universal Dependencies Project is presented in http://universaldependencies.org/.
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The annotated corpus can be downloaded from https://clarin.vdu.lt/xmlui/handle/20.500.11821/9.
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Acknowledgments
The authors thank the researchers from LLC Fotonija, especially Virginijus Dadurkevičius, for providing information about the Semantika.lt morphological analyzer.
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Kapočiūtė-Dzikienė, J., Rimkutė, E., Boizou, L. (2017). A Comparison of Lithuanian Morphological Analyzers. In: Ekštein, K., Matoušek, V. (eds) Text, Speech, and Dialogue. TSD 2017. Lecture Notes in Computer Science(), vol 10415. Springer, Cham. https://doi.org/10.1007/978-3-319-64206-2_6
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