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Lexical chaining has become an important part of many NLP tasks. However, the goodness of a chaining process and hence its annotation output depends on the quality of the chaining resource. Therefore, a framework for chaining is needed which integrates divergent resources in order to balance their deficits and to compare their strengths and weaknesses. In this paper we present an application that incorporates the framework of a meta model of lexical chaining exemplified on three resources and its generalized exchange format.