Using collective intelligence to detect pragmatic ambiguities

Abstract

This paper presents a novel approach for pragmatic ambiguity detection in natural language (NL) requirements specifications defined for a specific application domain. Starting from a requirements specification, we use a Web-search engine to retrieve a set of documents focused on the same domain of the specification. From these domain-related documents, we extract different knowledge graphs, which are employed to analyse each requirement sentence looking for potential ambiguities. To this end, an algorithm has been developed that takes the concepts expressed in the sentence and searches for corresponding “concept paths” within each graph. The paths resulting from the traversal of each graph are compared and, if their overall similarity score is lower than a given threshold, the requirements specification sentence is considered ambiguous from the pragmatic point of view. A proof of concept is given throughout the paper to illustrate the soundness of the proposed strategy.