  In this paper we describe the systems we developed for the English (lexical
and all-words) and Basque tasks. They were all supervised systems based on
Yarowsky's Decision Lists. We used Semcor for training in the English all-words
task. We defined different feature sets for each language. For Basque, in order
to extract all the information from the text, we defined features that have not
been used before in the literature, using a morphological analyzer. We also
implemented systems that selected automatically good features and were able to
obtain a prefixed precision (85%) at the cost of coverage. The systems that
used all the features were identified as BCU-ehu-dlist-all and the systems that
selected some features as BCU-ehu-dlist-best.
