Finally, a shallow−parser developed using these techniques will have to mirror the information contained in the training data.
for instance, if one trains such a tool on data were only non recursive NP chunks are marked 2 , then one will not be able to obtain richer information such as chunks of other categories, embeddings, syntactic functions... finite−state techniques rely on the development of a large set of rules (often based on regular expressions) to capture all the ways a constituent can expend.