[Context and motivation] The goal model is an essential model in Goal-Oriented Requirements Engineering. It is used to describe the system’s goals using a hierarchical structure in which high-level goals are refined into more specific ones.

[Question/problem] Constructing a goal model for a new application can present challenges, demanding considerable time and effort. Although there have been attempts to automate or semi-automate the construction of goal models, these tasks remain complex and manual.

[Principal ideas/results] This paper presents an interactive graphical tool that leverages a domain Knowledge Graph (KG) to assist the application designer in creating goals derived from this knowledge, thereby facilitating the creation of goal models. We use semantic similarity measurement and Natural Language Inference (NLI) to effectively extract and align triples from the KG with the high-level initial goals formulated by the application designer. The extracted triples undergo sentiment analysis and Graph-to-Text (G2T) generation to build meaningful subgoals. Nevertheless, processing KGs with Natural Language Processing (NLP) techniques can be a lengthy process. We introduce a restriction-based approach to bound the exploration of the KG to the most promising nodes. By tuning KG exploration bounds while using our tool in a case study, we analyze the trade-off between the quality of the resulting goal model and time performance, which is a key factor for an interactive approach.

[Contribution] Our paper highlights the relevance of our restriction-based approach to information retrieval in KGs to facilitate goal model generation.