Papers by Lukáš Kyjánek
Constructing a Lexical Resource of Russian Derivational Morphology (2022.lrec-1)
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| Challenge: | In Natural Language Processing of Russian, the inflection is satisfactorily processed, but there are only a few machine-trackable resources that capture derivations . |
| Approach: | They propose to use machine-learning methods to improve Russian inflection and derivational resources by using a database of more than 300 thousand lexemes and 164 thousand binary derivations. |
| Outcome: | The proposed method includes more than 300 thousand lexemes connected with more than 164 thousand binary derivational relations. |
Towards Universal Segmentations: UniSegments 1.0 (2022.lrec-1)
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Zdeněk Žabokrtský, Niyati Bafna, Jan Bodnár, Lukáš Kyjánek, Emil Svoboda, Magda Ševčíková, Jonáš Vidra
| Challenge: | Existing data resources for morphological segmentation are limited to 32 languages . a large number of word forms exist, with some sub-parts being "recycled" many times . |
| Approach: | They propose a multilingual data resource for morphological segmentation in 32 languages . they analyze diversity of how individual linguistic phenomena are captured across them . |
| Outcome: | The proposed scheme is based on 17 existing data resources relevant for segmentation in 32 languages. |
Web-based Annotation Interface for Derivational Morphology (2022.naacl-demo)
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| Challenge: | a visual interface for manual annotation of language resources for derivational morphology is created using relatively simple programming techniques. |
| Approach: | They propose a web-based visual interface for manual annotation of language resources for derivational morphology. |
| Outcome: | The proposed interface can be used for manual annotation of derivational morphology resources. |