Berend Gábor: Utilizing word embeddings for part-of-speech tagging.
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Abstract
In this paper, we illustrate the power of distributed word representations for the part-of-speech tagging of Hungarian texts. We trained CRF models for POS-tagging that made use of features derived from the sparse coding of the word embeddings of Hungarian words as signals. We show that relying on such a representation, it is possible to avoid the creation of language specific features for achieving reliable performance. We evaluated our models on all the subsections of the Szeged Treebank both using MSD and universal morphology tag sets. Furthermore, we also report results for inter-subcorpora experiments.
| Item Type: | Conference or Workshop Item |
|---|---|
| Journal or Publication Title: | Magyar Számítógépes Nyelvészeti Konferencia |
| Date: | 2016 |
| Volume: | 12 |
| ISBN: | 978-963-306-450-4 |
| Page Range: | pp. 59-67 |
| Event Title: | Magyar Számítógépes Nyelvészeti Konferencia (12.) (2016) (Szeged) |
| Related URLs: | http://acta.bibl.u-szeged.hu/58553/ |
| Uncontrolled Keywords: | Nyelvészet - számítógép alkalmazása |
| Additional Information: | Bibliogr.: p. 66-67. ; összefoglalás angol nyelven |
| Date Deposited: | 2019. Jul. 01. 08:51 |
| Last Modified: | 2022. Nov. 08. 11:49 |
| URI: | http://acta.bibl.u-szeged.hu/id/eprint/58962 |
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