Dealing with behavioral ambiguity in textual process descriptions

Abstract

Textual process descriptions are widely used in organizations since they can be created and understood by virtually everyone. The inherent ambiguity of natural language, however, impedes the automated analysis of textual process descriptions. While human readers can use their context knowledge to correctly understand statements with multiple possible interpretations, automated analysis techniques currently have to make assumptions about the correct meaning. As a result, automated analysis techniques are prone to draw incorrect conclusions about the correct execution of a process. To overcome this issue, we introduce the concept of a behavioral space as a means to deal with behavioral ambiguity in textual process descriptions. A behavioral space captures all possible interpretations of a textual process description in a systematic manner. Thus, it avoids the problem of focusing on a single interpretation. We use a compliance checking scenario and a quantitative evaluation with a set of 47 textual process descriptions to demonstrate the usefulness of a behavioral space for reasoning about a process described by a text. Our evaluation demonstrates that a behavioral space strikes a balance between ignoring ambiguous statements and imposing fixed interpretations on them.