Automatic extraction of glossary terms from natural language requirements

Abstract

We present a method for the automatic extraction of glossary terms from unconstrained natural language requirements. The glossary terms are identified in two steps - a) compute units (which are candidates for glossary terms) b) disambiguate between the mutually exclusive units to identify terms. We introduce novel linguistic techniques to identify process nouns, abstract nouns and auxiliary verbs. The identification of units also handles co-ordinating conjunctions and adjectival modifiers. This requires solving co-ordination ambiguity and adjectival modifier ambiguity. The identification of terms among the units adapts an in-document statistical metric. We present an evaluation of our method over a real-life set of software requirements' documents and compare our results with that of a base algorithm. The intricate linguistic classification and the tackling of ambiguity result in superior performance of our approach over the base algorithm.