Our first model for word sense disambiguation is Most Frequent Sense model, in which, as the name suggests, we choose most frequent sense for each word from the senses in a labelled corpus. For wordnet, this corresponds to the first sense in synset(). Using synset() and definition(), find the sense for each word. Evaluate and report the results using precision, recall and F-score