KernelTagger – a PoS Tagger for Very Small Amount of Training Data
| Autoři | |
|---|---|
| Rok publikování | 2017 |
| Druh | Článek ve sborníku |
| Konference | Proceedings of the Eleventh Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2017 |
| Fakulta / Pracoviště MU | |
| Citace | |
| www | |
| Obor | Informatika |
| Klíčová slova | PoS tagging; morphological tagging; language model; Czech |
| Popis | The paper describes a new Part of speech (PoS) tagger which can learn a PoS tagging language model from very short annotated text with the use of much bigger non-annotated text. Only several sentences could be used for training to achieve much better accuracy than a baseline. The results cannot be compared to the results of state-of-the-art taggers but it could be used during the annotation process for a pre-annotation. |
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