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A major challenge in Office Automation is one of automating routine jobs that involve large-scale processing of ill-formed natural language data. Such data are often present in documents such as forms where it is necessary and/or practical to allow latitude in how the forms may be filled. In this paper, we describe a computational model designed to process free-form textual data in application forms for Letters of Credit (LC), which represent a common vehicle for initiating international trade transactions. The model is based on a variation of the case-frame or thematic-role frame instantiation methods. We describe the implementation of the model, report empirical results with real LC applications, and indicate directions we are currently pursuing to improve its performance.

Automating review of forms for international trade transactions: a natural language processing approach