In this paper, we study the design of domain lexicons and address the problems of lexical knowledge representation and linking between different knowledge sources. A domain lexicon contains substantial domain specific vocabularies with associated phonological, morphological, syntactic and semantic/pragmatic information as well as links to general knowledge bases which are rich enough to support knowledge-intensive models for practical NLP systems. We take financial domain as an example to

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... rate the representation structures for syntactic and semantic knowledge. In order to suit for both maximal reusability and deep analysis, our domain lexicon is designed with uniform knowledge representation and fine-grain feature encoding. We also address the issues of how to bridge the gaps between coarse-grain general lexicons and fine-grain domain lexicons.