Cross-lingual Inflection as a Data Augmentation Method for Parsing
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http://hdl.handle.net/2183/36647
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- Investigación (FFIL) [853]
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Cross-lingual Inflection as a Data Augmentation Method for ParsingData
2022-05Cita bibliográfica
Alberto Muñoz-Ortiz, Carlos Gómez-Rodríguez, and David Vilares. 2022. Cross-lingual Inflection as a Data Augmentation Method for Parsing. In Proceedings of the Third Workshop on Insights from Negative Results in NLP, pages 54–61, Dublin, Ireland. Association for Computational Linguistics.
Resumo
[Absctract]: We propose a morphology-based method for low-resource (LR) dependency parsing. We train a morphological inflector for target LR languages, and apply it to related rich-resource (RR) treebanks to create cross-lingual (x-inflected) treebanks that resemble the target LR language. We use such inflected treebanks to train parsers in zero- (training on x-inflected treebanks) and few-shot (training on x-inflected and target language treebanks) setups. The results show that the method sometimes improves the baselines, but not consistently.
Palabras chave
Cross-lingual inflection
Morphological Inflection
Data augmentation
Dependency parsing
Low-resource languages
Syntactic data augmentation
Morphological Inflection
Data augmentation
Dependency parsing
Low-resource languages
Syntactic data augmentation
Descrición
Held 26 May 2022, Dublin, Ireland.
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Atribución 3.0 España
