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Timeline summarization (TLS) involves creating summaries of long-runningevents using dated summaries from numerous news articles. However, limited dataavailability has significantly slowed down the development of timelinesummarization. In this paper, we introduce the CNTLS dataset, a versatileresource for Chinese timeline summarization. CNTLS encompasses 77 real-lifetopics, each with 2524 documents and summarizes nearly 60\% days durationcompression on average all topics.  We meticulously analyze the corpus using well-known metrics, focusing on thestyle of the summaries and the complexity of the summarization task.Specifically, we evaluate the performance of various extractive and generativesummarization systems on the CNTLS corpus to provide benchmarks and supportfurther research. To the best of our knowledge, CNTLS is the first Chinesetimeline summarization dataset. The dataset and source code arereleased\footnote{Code and data available at:\emph{\url{https://github.com/OpenSUM/CNTLS}}.}.

CNTLS: A Benchmark Dataset for Abstractive or Extractive Chinese Timeline Summarization