Extracting ontological relationships (e.g., isa and hasa)
from free-text repositories (e.g., engineering documents, instruc-
tion manuals) can improve users' queries, as well as benefit-ing
applications built for these domains.

Current methods to extract ontologies from text usually fail to
capture many meaningful relationships because they concentrate on
single-word-terms or very short phrases.

We propose a novel pattern-based algorithm to fi nd onto- logical
relationships between complex concepts by exploiting parsing
information to extract concepts consisting of multi- word and nested
phrases. Our procedure is iterative: we tailor the constrained
sequential pattern mining framework to discover new patterns. Our
experiments on three real data sets show that our algorithm
consistently and signifi cantly outperforms previous representative
ontology extraction algorithms.