A harmonised testsuite for POS tagging of German social media data
We present a testsuite for POS tagging German web data. Our testsuite provides the original raw text as well as the gold tokenisations and is annotated for parts-of-speech. The testsuite includes a new dataset for German tweets, with a current size of 3,940 tokens. To increase the size of the data,...
Gespeichert in:
| Hauptverfasser: | , , |
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| Dokumenttyp: | Kapitel/Artikel Konferenzschrift |
| Sprache: | Deutsch |
| Veröffentlicht: |
29.09.2018
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| In: |
The 27th International Conference on Computational Linguistics - proceedings of the conference
Year: 2018, Pages: 18-28 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://ids-pub.bsz-bw.de/frontdoor/index/index/year/2018/docId/7931
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| Verfasserangaben: | Ines Rehbein, Josef Ruppenhofer, Victor Zimmermann |
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| 520 | |a We present a testsuite for POS tagging German web data. Our testsuite provides the original raw text as well as the gold tokenisations and is annotated for parts-of-speech. The testsuite includes a new dataset for German tweets, with a current size of 3,940 tokens. To increase the size of the data, we harmonised the annotations in already existing web corpora, based on the Stuttgart-Tübingen Tag Set. The current version of the corpus has an overall size of 48,344 tokens of web data, around half of it from Twitter. We also present experiments, showing how different experimental setups (training set size, additional out-of-domain training data, self-training) influence the accuracy of the taggers. All resources and models will be made publicly available to the research community. | ||
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