KernelTagger – a PoS Tagger for Very Small Amount of Training Data
| Authors | |
|---|---|
| Year of publication | 2017 |
| Type | Article in Proceedings |
| Conference | Proceedings of the Eleventh Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2017 |
| MU Faculty or unit | |
| Citation | |
| Web | |
| Field | Informatics |
| Keywords | PoS tagging; morphological tagging; language model; Czech |
| Description | 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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