Cross-lingual zero-shot dependency parsing
3 papers with code • 1 benchmarks • 1 datasets
Cross-lingual zero-shot parsing is the task of inferring the dependency parse of sentences from one language without any labeled training trees for that language.
Description from NLP Progress
Benchmarks
These leaderboards are used to track progress in Cross-lingual zero-shot dependency parsing
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Universal Dependencies
Most implemented papers
Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing
TalSchuster/CrossLingualELMo
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NAACL 2019
We introduce a novel method for multilingual transfer that utilizes deep contextual embeddings, pretrained in an unsupervised fashion.
Many Languages, One Parser
We train one multilingual model for dependency parsing and use it to parse sentences in several languages.
On the Relation between Syntactic Divergence and Zero-Shot Performance
We explore the link between the extent to which syntactic relations are preserved in translation and the ease of correctly constructing a parse tree in a zero-shot setting.
