Typological Distance and Robustness in Zero-Shot Cross-Lingual Semantic Parsing

The availability of corpora to train semantic parsers in English has lead to significant advances in the field. Unfortunately, for languages other than English, annotation is scarce and so are developed parsers. We then ask: could a parser trained in English be applied to language that it hasn't been trained on? To answer this question we explore zero-shot cross-lingual semantic parsing where we train an available coarse-to-fine semantic parser (Liu et al., 2018) using cross-lingual word embeddings and universal dependencies in English and test it on Italian, German and Dutch. Results on the P

Research goal: Does the typological distance between source (English) and target languages affect the robustness of zero-shot cross-lingual semantic parsing when tested on adversarial or low-resource language benchmarks, and can this be quantified using metrics like BLEU or SPARQL execution accuracy?

Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 7.8/10.