Papers by Alymzhan Toleu
Language-Independent Approach for Morphological Disambiguation (2022.coling-1)
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| Challenge: | Existing approaches for predicting complex morphological tags treat each analysis as a tag and apply sequence labeling models to perform tagging. |
| Approach: | They propose a language-independent approach which integrates all words, roots, POS and morpheme tags into vectors and computes the inner products between analyses and the contexts. |
| Outcome: | The proposed approach outperforms existing models on seven different languages while running about 6 and 33 times faster than MarMot and Seq2Seq, respectively. |