Recently semantic parsing in context has received considerable attention,
which is challenging since there are complex contextual phenomena. Previous
works verified their proposed methods in limited scenarios, which motivates us
to conduct an exploratory study on context modeling methods under real-world
semantic parsing in context. We present a grammar-based decoding semantic
parser and adapt typical context modeling methods on top of it. We evaluate 13
context modeling methods on two large complex cross-domain datasets, and our
best model achieves state-of-the-art performances on both datasets with
significant improvements. Furthermore, we summarize the most frequent
contextual phenomena, with a fine-grained analysis on representative models,
which may shed light on potential research directions. Our code is available at
this https URL

本文对语境建模方法在真实语义解析中的应用进行了探究，并提出了一种基于语法解码的语义解析器，适用于各种复杂领域。我们评估了 13 种语境建模方法，分析了最常见的语境现象，发现最佳模型在两个大型跨领域数据集上都取得了最先进的性能表现。