Accurate SHRG-Based Semantic Parsing
Yufei Chen, Weiwei Sun, Xiaojun Wan · 2018
We demonstrate that an SHRG-based parser can produce semantic graphs much more accurately than previously shown, by relating synchronous production rules to the syntacto-semantic composition process.Our parser achieves an accuracy of 90.35 for EDS (89.51 for DMRS) in terms of ELEMENTARY DEPENDENCY MATCH, which is a 4.87 (5.45) point improvement over the best existing data-driven model, indicating, in our view, the importance of linguistically-informed derivation for data-driven semantic parsing.This accuracy is equivalent to that of English Resource Grammar guided models, suggesting that (recurrent) neural network models are able to effectively learn deep linguistic knowledge from annotations.