| Autor: |
Hour Kaing, Chenchen Ding, Masao Utiyama, Eiichiro Sumita, Katsuhito Sudoh, Satoshi Nakamura |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
IEEE Access, Vol 9, Pp 141571-141578 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2021.3120382 |
| Popis: |
Cross-lingual transfer is an important technique for low-resource language processing. Temporarily, most research on syntactic parsing works on the dependency structures. This work investigates cross-lingual parsing on another type of important syntactic structure, i.e., the constituency structure. We propose a delexicalized approach, where part-of-speech sequences of rich-resource languages are used to train cross-lingual models to parse low-resource languages. We also investigate the measurements on the selection of proper rich-resource languages for specific low-resource languages. The experiments show that the delexicalized approach outperforms state-of-the-art unsupervised models on six languages by a margin of 4.2 to 37.0 of sentence-level F1-score. Based on the experiment results, the limitation and future work of the delexicalized approach are discussed. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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