Before splitting the data into train, dev and test sets, we theorized that having too similar documents in the train and the test sets could lead to a skewed (too optimistic) evaluation of any supervised summarization methods.
the following documents were dropped: • with empty headline; • with abstract shorter than 10 words; • with full text shorter than 100 words; • with text-to-abstract ratio less than 4.