Papers by Alexandra Ivoylova
Applying Natural Annotation and Curriculum Learning to Named Entity Recognition for Under-Resourced Languages (2022.coling-1)
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| Challenge: | Existing approaches to build NLP models for low-resourced languages rely on machine translation or cross-lingual transfer. |
| Approach: | They propose to use natural annotations to build synthetic training sets from resources not originally designed for the target downstream task. |
| Outcome: | The proposed model achieves the F1 score of 0.78 for Belarusian starting from zero resources compared to the baseline of 0.63 for English . the proposed model can be fine-tuned to reflect linguistic properties, such as the grammatical case and gender, for the Slavic languages. |