论文标题
无监督的双重解释，以进行两阶段的语义解析
Unsupervised Dual Paraphrasing for Two-stage Semantic Parsing
论文作者
论文摘要
语义解析的一个艰巨的问题是注释的稀缺性。为了减少非平凡的人工劳动，我们提出了一个两阶段的语义解析框架，第一阶段利用无监督的释义模型将不标记的自然语言话语转换为规范的话语。下游天真的语义解析器接受中间输出并返回目标逻辑形式。此外，整个训练过程分为两个阶段：预训练和循环学习。在整个训练中都引入了三个量身定制的自我监督任务，以激活无监督的释义模型。一夜之间的基准测试结果的实验结果表明，我们的框架与监督培训有效且兼容。
One daunting problem for semantic parsing is the scarcity of annotation. Aiming to reduce nontrivial human labor, we propose a two-stage semantic parsing framework, where the first stage utilizes an unsupervised paraphrase model to convert an unlabeled natural language utterance into the canonical utterance. The downstream naive semantic parser accepts the intermediate output and returns the target logical form. Furthermore, the entire training process is split into two phases: pre-training and cycle learning. Three tailored self-supervised tasks are introduced throughout training to activate the unsupervised paraphrase model. Experimental results on benchmarks Overnight and GeoGranno demonstrate that our framework is effective and compatible with supervised training.
