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.

翻译：人们越来越有兴趣将人工智能(AI)纳入国防和军事系统,以补充和增强人类的智能和能力,然而,要实现有效的人力机器伙伴关系还需要做大量工作,这项工作的目的是通过发展将人类自然语言自动翻译成一种机器可理解的语言(例如SQL查询)的能力,加强人类机器的通信能力。实现这一目标的技术通常包括建立一个语言解析器,对大量高质量的人工附加说明的数据进行培训。然而,在许多现实世界的防御假设中,获取如此大量的培训数据是行不通的。就我们所知,很少有工作试图探索用有限的手动解析数据(换言之,零光)来培训一个语言解析器的可能性。在本文中,我们研究如何利用自动生成大型培训数据集(以语言解说式表述及其相应的逻辑形式在SQL格式中)的解析方法,并用海洋领域的实体数据介绍我们的实验结果。</s>