Deeper error analysis of Lithuanian morphological analyzers
Author | Affiliation | |
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LT | ||
LT | ||
LT |
Date |
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2018 |
In this research we continue the intrinsic evaluation of two the most popular and publicly available Lithuanian morphological analyzers-lemmatizers Lemuoklis and Semantika.lt. In our previous paper [1] we reported the comparative results of the shallow morphological analysis mostly covering coarse-grained part-of-speech tags. The results were better for Semantika.lt on 3 domains (administrative, fiction and periodicals), but not on the scientific texts. The deeper analysis of the fine-grained morphological categories (case, gender, number, degree, tense, mood, person, and voice) gave a more precise account of the strengths and weaknesses of both analyzers. Further investigations showed that the higher performance of Lemuoklis analyzer on the scientific domain is probably related to a more successful analyse of long distance agreements, in a spite of an overall slight superiority of Semantika.lt analyzer.
Knygos ISBN 978-1-61499-912-6 (online)
Journal | Cite Score | SNIP | SJR | Year | Quartile |
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Frontiers in Artificial Intelligence and Applications | 0.6 | 0.354 | 0.19 | 2018 | Q4 |