  Bilingual machine-readable dictionaries are knowledge resources useful in
many automatic tasks. However, compared to monolingual computational lexicons
like WordNet, bilingual dictionaries typically provide a lower amount of
structured information, such as lexical and semantic relations, and often do
not cover the entire range of possible translations for a word of interest. In
this paper we present Cycles and Quasi-Cycles (CQC), a novel algorithm for the
automated disambiguation of ambiguous translations in the lexical entries of a
bilingual machine-readable dictionary. The dictionary is represented as a
graph, and cyclic patterns are sought in the graph to assign an appropriate
sense tag to each translation in a lexical entry. Further, we use the
algorithms output to improve the quality of the dictionary itself, by
suggesting accurate solutions to structural problems such as misalignments,
partial alignments and missing entries. Finally, we successfully apply CQC to
the task of synonym extraction.
