WoPeD (Workflow Petrinet Designer) is an open-source Java software for designing business processes in terms of workflow nets, a common extension of Petri nets. This demo lays the focus on two recently added features making use of Natural Language Processing (NLP) algorithms in order support the conversion of a graphical process model into a textual process description and vice versa.
NLP and BPM Graphical process modeling languages have become an industry standard, allowing various stakeholders to collectively create visual process descriptions on a conceptual level. However, graphical models frequently co-exist with informal textual process descriptions, be it for lack of skills or tools or time to create
a graphical model or because a text-based description is required for a process handbook as sometimes mandated by QA agencies. This has brought up the question in BPM research transforming these two process representations into each other, i.e. to automatically generate the textual equivalent of a given graphical process model and to automatically generate an appealing visual process model from a given textual representation. There are interesting practical use cases for this functionality, e.g. to check the mutual compliance between a textual and graphical version of a business process or to facilitate the inclusion of visually impaired persons in process modelling activities by providing them with a text-based interface for understanding and describing a business process. The following two sections give an overview of how NLP algorithms have been integrated into WoPeD: Firstly, to export the current process editor contents into readable English text (“Process2Text”) and secondly to synthetize an workflow net from a given verbal process specification (“Text2Process”). 3
In [
The analysis is done by two freely available standard NLP tools, Stanford Tagger2 and WordNet3. The result is converted into a Refined Process Structure Tree (RPST), a generic data structure to represent components of a process
graph being introduced in more detail e.g. in [
The implementation in WoPeD takes major parts of the solution presented
in [
The opposite direction of the transformation is based on an algorithm
welldocumented e.g. in [
This mainly identifies the semantically relevant elements of the textual process model (e.g. actors, actions, business objects). The result is written into a data structure called WorldModel where all contributing model elements and their interrelations are stored. The WorldModel is converted into PNML, the standard XML-based representation for workflow nets. The last step is to open up a new WoPeD editor window and create coordinates for the automatically generated model by calling WoPeD’s built-in layout beautifier. Figure 3 roughly visualizes the algorithm. Figure 4 shows a screenshot of the dialog for entering the textual process description (either by typing in or by uploading a text file) and below the resulting auto-generated and auto-layouted workflow net. 5
The above features are still in an experimental stage suffering from the general problem of semantical ambiguities in natural language processing in both directions. However, the plan is to improve the transformation quality in future releases of WoPeD. The software is open source and can be downloaded from the homepage5 or directly from Sourceforge6.