A Simple yet Effective Joint Training Method for Cross-Lingual Universal Dependency Parsing
This paper describes Fudan{'}s submission to CoNLL 2018{'}s shared task Universal Dependency Parsing. We jointly train models when two languages are similar according to linguistic typology and then ensemble the models using a simple re-parse algorithm. We outperform the baseline method by 4.4{\%} (2.1{\%}) on average on development (test) set in CoNLL 2018 UD Shared Task.
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