CATAMARAN_v1.json

Cross-lingual summarization, which produces a summary in one language from a given source document in another language, could be extremely helpful for humans to obtain information across the world. However, it is still a little-explored task due to the lack of cross-lingual summarization datasets. CATAMARAN is the first high-quality cross-lingual long text abstractive summarization dataset. It is crawled from the New York Times Chinese and English websites and contains about 20,000 parallel news articles and corresponding summaries, all written by humans. The average length of articles is 1133.65 for English articles and 2035.33 for Chinese articles, and the average length of the summaries is 26.59 and 70.05, respectively.