Decoupling Structure and Lexicon for Zero-Shot Semantic Parsing
Table 2: Test accuracy for all models on all domains.
['Model', 'Blocks', 'Calendar', 'Housing', 'Publications', 'Recipes', 'Restaurants', 'Social', 'Avg.']
We trained all models above and evaluated on the test set for all seven domains. CrossLex performs poorly, as it can only generate KB constants seen during training. CrossLexRep performs better, as it can generate KB constants from the target domain, however, generating the correct constant usually fails. This highlights the challenge in the zero-shot semantic parsing setting.