Exploiting Rich Syntactic Information for Semantic Parsing with Graph-to-Sequence Model
Table 3: Evaluation results on ATIS where Accori and Accpara denote the accuracy on the original and paraphrased development set of ATIS, respectively.
['Feature', 'Acc [ITALIC] ori', 'Acc [ITALIC] para', 'Diff.']
We also report the result of our model on the original ATIS development set. We can see that (1) no matter which feature our model uses, the performance degrades at least 2.5% on the paraphrased dataset; (2) the model that only uses word order features achieves the worst robustness to the paraphrased queries while the dependency feature seems more robust than other two features. (3) simultaneously utilizing three syntactic features could greatly enhance the robustness of our model. These results again demonstrate that our model could benefit from incorporating more aspects of syntactic information.