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Multilingual Projection for Parsing Truly Low-Resource Languageš

Abstract : We propose a novel approach to cross-lingual part-of-speech tagging and dependency parsing for truly low-resource languages. Our annotation projection-based approach yields tagging and parsing models for over 100 languages. All that is needed are freely available parallel texts, and taggers and parsers for resource-rich languages. The empirical evaluation across 30 test languages shows that our method consistently provides top-level accuracies , close to established upper bounds, and outperforms several competitive baselines.
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Contributor : Héctor Martínez Alonso Connect in order to contact the contributor
Submitted on : Wednesday, January 4, 2017 - 7:34:10 PM
Last modification on : Tuesday, October 25, 2022 - 6:56:20 PM
Long-term archiving on: : Wednesday, April 5, 2017 - 3:30:16 PM


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  • HAL Id : hal-01426754, version 1


Zeljko Agic, Anders Johannsen, Barbara Plank, Héctor Martínez Alonso, Natalie Schluter, et al.. Multilingual Projection for Parsing Truly Low-Resource Languageš. Transactions of the Association for Computational Linguistics, 2016. ⟨hal-01426754⟩



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