In the realm of software applications in the transportation industry, Domain-Specific Languages (DSLs) have enjoyed widespread adoption due to their ease of use and various other benefits. With the ceaseless progress in computer performance and the rapid development of large-scale models, the possibility of programming using natural language in specified applications - referred to as Application-Specific Natural Language (ASNL) - has emerged. ASNL exhibits greater flexibility and freedom, which, in turn, leads to an increase in computational complexity for parsing and a decrease in processing performance. To tackle this issue, our paper advances a design for an intermediate representation (IR) that caters to ASNL and can uniformly process transportation data into graph data format, improving data processing performance. Experimental comparisons reveal that in standard data query operations, our proposed IR design can achieve a speed improvement of over forty times compared to direct usage of standard XML format data.

翻译：在交通行业的软件应用领域，领域特定语言（DSLs）因其易用性及其他诸多优势而得到广泛应用。随着计算机性能的持续进步和大规模模型的快速发展，在特定应用中使用自然语言进行编程（称为应用特定自然语言，ASNL）的可能性已经出现。ASNL展现出更强的灵活性和自由度，但这同时也导致解析计算复杂度的增加和处理性能的下降。为解决这一问题，本文提出了一种面向ASNL的中间表示（IR）设计方案，该方案能够将交通数据统一处理为图数据格式，从而提升数据处理性能。实验对比表明，在标准数据查询操作中，与直接使用标准XML格式数据相比，我们提出的IR设计能够实现超过四十倍的速度提升。