Mutlitask Learning for Cross-Lingual Transfer of Semantic Dependencies

Understand

We describe a method for developing broad-coverage semantic dependency parsers for languages for which no semantically annotated resource is available.

• We leverage a multitask learning framework coupled with an annotation projection method.
• We transfer supervised semantic dependency parse annotations from a rich-resource language to a low-resource language through parallel data, and train a semantic parser on projected data.
• We make use of supervised syntactic parsing as an auxiliary task in a multitask learning framework, and show that with different multitask learning settings, we consistently improve over the single-task baseline.