Stagger: an Open-Source Part of Speech Tagger for Swedish
This work presents Stagger, a new open-source part of speech tagger for Swedish based on the Averaged Perceptron. By using the SALDO morphological lexicon and semi-supervised learning in the form of Collobert andWeston embeddings, it reaches an accuracy of 96.4% on the standard Stockholm-Umeå Corpu...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
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Linköping University Electronic Press
2013-09-01
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| Series: | Northern European Journal of Language Technology |
| Online Access: | https://nejlt.ep.liu.se/article/view/1653 |
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| Summary: | This work presents Stagger, a new open-source part of speech tagger for Swedish based on the Averaged Perceptron. By using the SALDO morphological lexicon and semi-supervised learning in the form of Collobert andWeston embeddings, it reaches an accuracy of 96.4% on the standard Stockholm-Umeå Corpus dataset, making it the best single part of speech tagging system reported for Swedish. Accuracy increases to 96.6% on the latest version of the corpus, where the annotation has been revised to increase consistency. Stagger is also evaluated on a new corpus of Swedish blog posts, investigating its out-of-domain performance.
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| ISSN: | 2000-1533 |