Statistical parsing of messages

Abstract

The recent trend in natural language processing research has been to develop systems that deal with text concerning small, well defined domains. One practical application for such systems is to process messages pertaining to some very specific task or activity [5]. The advantage of dealing with such domains is twofold - firstly, due to the narrowness of the domain, it is possible to encode most of the knowledge related to the domain and to make this knowledge accessible to the natural language processing system, which in turn can use this knowledge to disambiguate the meanings of the messages. Secondly, in such a domain, there is not a great diversity of language constructs and therefore it becomes easier to construct a grammar which will capture all the constructs which exist in this sub-language.