  This paper presents a method that combines a set of unsupervised algorithms
in order to accurately build large taxonomies from any machine-readable
dictionary (MRD). Our aim is to profit from conventional MRDs, with no explicit
semantic coding. We propose a system that 1) performs fully automatic exraction
of taxonomic links from MRD entries and 2) ranks the extracted relations in a
way that selective manual refinement is allowed. Tested accuracy can reach
around 100% depending on the degree of coverage selected, showing that taxonomy
building is not limited to structured dictionaries such as LDOCE.
