Learning to Summarize Passages: Mining Passage-Summary Pairs from Wikipedia Revision Histories
Table 2: A comparison of current summarization datasets and Psg2Sum.
['[BOLD] Dataset', '[BOLD] Granularity', '[BOLD] Domain', '[BOLD] Corpus Size', '[BOLD] avg. Input Length sentences', '[BOLD] avg. Input Length words', '[BOLD] Output Length sentences', '[BOLD] Output Length words', '[BOLD] Reference  [BOLD] Number']
Recently, newswire websites such as CNN, Daily Mail and NY Times have been used as sources for single document summarization. However, it is bias toward extractive strategies, and limited work has used this dataset for summarization Grusky et al. CNN and Daily Mail Hermann et al. These datasets have been used for summarization as is See et al. Additionally, some systems mix CNN and Daily Mail as training data Nallapati et al. ; See et al. Paulus et al. Therefore, it would be challenging for systems to make comparisons considering that previous works are using different versions of datasets. All the above-mentioned datasets, including both the sentence level and the document level summarization datasets, are constructed or labeled using the newswire source, which leads to the fact that they are all in the news domain. The proposed Psg2Sum is constructed with the open-domain Wikipedia Chen et al. As far as we know, this is the first open-domain text summarization dataset. To the best of our knowledge, Psg2Sum is the first passage-to-summary dataset, which is with the same magnitude with the current frequently used CNN and Daily Mail datasets. The average input length of Psg2Sum is 4.83 sentences (118.26 words), compared with the average length 33.98 sentences (760.50 words) of CNN and 29.33 sentences (653.33 words) of Daily Mail corpus.