There has been an increasing interest in incorporating Artificial
Intelligence (AI) into Defence and military systems to complement and augment
human intelligence and capabilities. However, much work still needs to be done
toward achieving an effective human-machine partnership. This work is aimed at
enhancing human-machine communications by developing a capability for
automatically translating human natural language into a machine-understandable
language (e.g., SQL queries). Techniques toward achieving this goal typically
involve building a semantic parser trained on a very large amount of
high-quality manually-annotated data. However, in many real-world Defence
scenarios, it is not feasible to obtain such a large amount of training data.
To the best of our knowledge, there are few works trying to explore the
possibility of training a semantic parser with limited manually-paraphrased
data, in other words, zero-shot. In this paper, we investigate how to exploit
paraphrasing methods for the automated generation of large-scale training
datasets (in the form of paraphrased utterances and their corresponding logical
forms in SQL format) and present our experimental results using real-world data
in the maritime domain.

本文研究通过开发将人类自然语言自动翻译为机器可理解语言的能力，从而增强人机交流效率，重点是如何利用传统方法训练有限的数据集训练语义解析器，在海事领域的实验结果表明被翻译成 SQL 格式的语句和逻辑方面的形式是一种有用的训练数据集。