A lightweight semantic chunking model based on tagging
Kadri Hacıoğlu · 2004
In this paper, a framework for the development of a fast, accurate, and highly portable semantic chunker is introduced.The framework is based on a non-overlapping, shallow tree-structured language.The derivation of the tree is considered as a sequence of tagging actions in a predefined linguistic context, and a novel semantic chunker is accordingly developed.It groups the phrase chunks into the arguments of a given predicate in a bottom-up fashion.This is quite different from current approaches to semantic parsing or chunking that depend on full statistical syntactic parsers that require tree bank style annotation.We compare it with a recently proposed word-byword semantic chunker and present results that show that the phrase-by-phrase approach performs better than its word-by-word counterpart.