We have also experimented with a very simple method for handling ambiguity in our bootstrapping algorithm: when augmenting the seed set, instead of labeling a word with a tag that receives 9 votes from the 45 pairwise classifiers, we label a word with any tag that receives at least 8 votes, effectively allowing the assignment of more than one label to a word.
our experimental results (not shown due to space limitations) indicate that the incorporation of this method does not yield better overall performance, since many of the additional labels are erroneous and hence their presence deteriorates the quality of the bootstrapped data.