NP Chunking using ILP

This is to report the results of approaching the problem of NP chunking using Inductive Logic Programming techniques. The problem, as defined in (Ramshaw and Marcus, 1995), is the machine learning of rules that recognise nonrecursive, base NPs in text annotated with partof -speech tags, by tagging each word as being `inside' or `outside' an NP. (Consecutive NPs are appropriately treated.) The same input data as in the original experiment is used here, but the machine learning technique is Inductive Logic Programming, and more specifically the Progol algorithm. The problem is formulated as the machine learning of a Prolog predicate that will accept a partof -speech tagged word and its context as input and associate it with the appropriate syntactic tag. 1 Introduction Text chunking amounts to identifying nonoverlapping constituents in a sentence, without assigning internal structure to them. It is useful either as a preprocessing stage for full parsing or in the context of shallow pa..