Process modeling is a sub-domain of Business Process Management (BPM) focused on the translation of process artifacts into formal models. This task traditionally requires extensive human input and domain expertise in both BPM notations and the specific business context. While Large Language Models (LLMs) can now automate much of this manual work, current text-to-model approaches focus predominantly on the control-flow perspective-ordering activities without considering the collaborative aspect of the processes. In this paper, we introduce a resource-aware generation pipeline that produces formal BPMN 2.0 collaboration diagrams from natural-language descriptions. Rather than solely prompting an LLM for raw XML, we describe a compact, executable intermediate language with mandatory resource details defining both the organization (pool) and the role (lane). Cross-organization dependencies are materialized using the standard formal notation for such interactions-message events-while an orthogonal layout routine automatically handles the spatial arrangement of elements within pools and lanes. Experiments on ten business processes with nine LLMs show strong resource discovery while preserving control-flow quality and adding only marginal runtime overhead. This approach moves generative modeling toward a more comprehensive, multi-collaborative representation of business operations.

翻译：流程建模是业务流程管理（BPM）的一个子领域，专注于将流程产物转化为形式化模型。传统上，这项任务需要大量人工输入，并要求在BPM符号体系及特定业务场景方面具备深厚的领域专业知识。虽然大语言模型（LLM）现在能自动化处理大部分人工工作，但当前从文本到模型的方法主要侧重于控制流视角——即活动排序，而未考虑流程的协作层面。本文提出一种资源感知的生成流水线，能够根据自然语言描述生成正式的业务流程模型与符号（BPMN）2.0协作图。我们并非仅提示LLM生成原始XML，而是描述了一种紧凑、可执行的中间语言，其中包含强制性资源细节，用以定义组织（泳池）和角色（泳道）。跨组织依赖关系通过标准形式化符号（即消息事件）的具体化实现，而正交布局程序则自动处理泳池和泳道内元素的空间排列。基于十个业务流程及九个LLM的实验表明，该方法在保持控制流质量并仅带来微小运行时开销的同时，展现出强大的资源发现能力。该方案推动生成式建模迈向业务操作中更全面、多协作的表达。