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Ensuring Action: Identifying Unclear Actor Specifications in Textual Business Process Descriptions

机译:确保行动:在文本业务流程描述中识别不明确的演员规范

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In many organisations, business process (BP) descriptions are available in the form of written procedures, or operational manuals. These documents are expressed in informal natural language, which is inherently open to different interpretations. Hence, the content of these documents might be incorrectly interpreted by those who have to put the process into practice. It is therefore important to identify language defects in written BP descriptions, to ensure that BPs are properly carried out. Among the potential defects, one of the most relevant for BPs is the absence of clear actors in action-related sentences. Indeed, an unclear actor might lead to a missing responsibility, and, in turn, to activities that are never performed. This paper aims at identifying unclear actors in BP descriptions expressed in natural language. To this end, we define an algorithm named ABIDE, which leverages rule-based natural language processing (NLP) techniques. We evaluate the algorithm on a manually annotated data-set of 20 real-world BP descriptions (1,029 sentences). ABIDE achieves a recall of 87%, and a precision of 56%. We consider these results promising. Improvements of the algorithm are also discussed in the paper.
机译:在许多组织中,业务流程(BP)描述可以书面程序或操作手册的形式提供。这些文件以非正式的自然语言表示,这本质上对不同的解释开放。因此,这些文件的内容可能被那些必须将流程放在实践中的人解释错误。因此,重要的是要识别书面BP描述中的语言缺陷,以确保正确执行BPS。在潜在的缺陷中,对BPS最相关的缺陷之一是在行动相关的句子中没有明确的演员。实际上,一个不明确的演员可能导致缺失的责任,而且反过来,从未表演过的活动。本文旨在识别自然语言表达的BP描述中的不明确的演员。为此,我们定义了一个名为abide的算法,它利用基于规则的自然语言处理(NLP)技术。我们在手动注释的20个现实世界BP描述(1,029个句子)上评估算法。遵循召回的召回量为87%,精度为56%。我们认为这些结果有希望。本文还讨论了算法的改进。

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