Phylogenic Multi-Lingual Dependency Parsing
| Autor: | Mathieu Dehouck, Pascal Denis |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Structure (mathematical logic)
Parsing Dependency (UML) Phylogenetic tree Computer science business.industry 02 engineering and technology 010501 environmental sciences computer.software_genre 01 natural sciences Tree (data structure) Rule-based machine translation Dependency grammar 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business computer Natural language processing 0105 earth and related environmental sciences |
| Zdroj: | NAACL-HLT (1) |
| DOI: | 10.18653/v1/n19-1017 |
| Popis: | Languages evolve and diverge over time. Their evolutionary history is often depicted in the shape of a phylogenetic tree. Assuming parsing models are representations of their languages grammars, their evolution should follow a structure similar to that of the phylo-genetic tree. In this paper, drawing inspiration from multi-task learning, we make use of the phylogenetic tree to guide the learning of multilingual dependency parsers leverag-ing languages structural similarities. Experiments on data from the Universal Dependency project show that phylogenetic training is beneficial to low resourced languages and to well furnished languages families. As a side product of phylogenetic training, our model is able to perform zero-shot parsing of previously unseen languages. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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