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- W3118343451 abstract "Cross-lingual and multilingual methods have been widely suggested as options for dependency parsing of low-resource languages; however, these typically require the use of annotated data in related high-resource languages. In this paper, we evaluate the performance of these methods versus monolingual parsing of Tagalog, an Austronesian language which shares little typological similarity with any existing high-resource languages. We show that a monolingual model developed on minimal target language data consistently outperforms all cross-lingual and multilingual models when no closely-related sources exist for a low-resource language." @default.
- W3118343451 created "2021-01-18" @default.
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- W3118343451 date "2020-12-01" @default.
- W3118343451 modified "2023-09-23" @default.
- W3118343451 title "Parsing in the absence of related languages: Evaluating low-resource dependency parsers on Tagalog" @default.
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