Computing with Words is an emerging paradigm in knowledge representation and information processing. It provides a mathematical model to represent the meaning of imprecise words and phrases in natural language and introduces advanced techniques to perform reasoning on inexact knowledge. Since its introduction, there have been many studies on computing with words but mostly from the theoretical point of view and the paradigm still lacks sufficient support from the software side. Our project is an attempt to fill this gap by presenting an enhanced inference engine toolkit for supporting computing with words. The scope of the presented toolkit, as opposed to many available fuzzy logic tools, goes beyond simple fuzzy-if-then rules and performs a chain of inferences on complex fuzzy propositions containing fuzzy arithmetics, fuzzy quantifiers, and fuzzy probabilities. It implements a powerful declarative language which allows users to express their knowledge in a more natural and convenient way and performs a chain of reasoning on imprecise propositions.

A GCL declarative language is developed to allow users to express their knowledge in form of generalized constraints and pose queries to a GCL knowledge base. The tool can benefit the researchers in fuzzy community as it allows them to automatically perform a chain of reasoning on a complex fuzzy knowledge base. It can also provide an opportunity to add CW to the syllabus of courses in soft computing and AI as it helps the students to explore the application of CW. The CW inference engine is implemented in java and utilizes Jess engine for pattern matching.