  This paper describes a hybrid system for WSD, presented to the English
all-words and lexical-sample tasks, that relies on two different unsupervised
approaches. The first one selects the senses according to mutual information
proximity between a context word a variant of the sense. The second heuristic
analyzes the examples of use in the glosses of the senses so that simple
syntactic patterns are inferred. This patterns are matched against the
disambiguation contexts. We show that the first heuristic obtains a precision
and recall of .58 and .35 respectively in the all words task while the second
obtains .80 and .25. The high precision obtained recommends deeper research of
the techniques. Results for the lexical sample task are also provided.
