UCD-PN: selecting general paraphrases using conditional probability

We describe a system which ranks human-provided paraphrases of noun compounds, where the frequency with which a given paraphrase was provided by human volunteers is the gold standard for ranking. Our system assigns a score to a paraphrase of a given compound according to the number of times it has co-occurred with other paraphrases in the rest of the dataset. We use these co-occurrence statistics to compute conditional probabilities to estimate a sub-typing or Is-A relation between paraphrases. This method clusters together paraphrases which have similar meanings and also favours frequent, general paraphrases rather than infrequent paraphrases with more specific meanings.