ATRANS: automatic processing of money transfer messages

Abstract

Unformatted natural-language nioney.transfer messages play an important role in the int~ernational banking system. Manually reading such messages and encoding them in the format understandable by a bank’s automsl,ic payment system is relatively slow and espensive. Due to the very restricted nature of the domain, the problem lends itself naturally to a Conceptual Dependency (CD), script,-st,yle solution. This paper illustrates the solutions to a number ol problems that arise when an acaclemic theory is applied to a real-world problem. In particular, we concentrate on the problem of context localization in the absence of reliable syntactic clues, such as sentence boundaries. I.