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# LCSTS |
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### Introduction |
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LCSTS is a Large-scale Chinese Short Text Summarization dataset constructed from the Chinese microblogging website SinaWeibo for the summary generation, which is collected by Harbin Institute of Technology. This corpus consists of over 2 million real Chinese short texts with short summaries given by the writer of each text, as well as 10,666 short summaries marked manually. |
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### Paper |
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[LCSTS: A Large Scale Chinese Short Text Summarization Dataset](https://www.aclweb.org/anthology/D15-1229.pdf). EMNLP 2015. |
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### Data Size |
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Training set: 2,400,591; Validation set: 8,685; Test set: 725. |
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### Data Format |
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Each instance is composed of a human-labeled summary quality score (human_label, an integer), input text (text, a string) and a output summary (summary, an integer). |
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### Example |
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``` |
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{ |
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"human_label": 5, |
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"summary": "林志颖公司疑涉虚假营销无厂房无研发", |
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"text": "日前,方舟子发文直指林志颖旗下爱碧丽推销假保健品,引起哗然。调查发现,爱碧丽没有自己的生产加工厂。其胶原蛋白饮品无核心研发,全部代工生产。号称有“逆生长”功效的爱碧丽“梦幻奇迹限量组”售价>高达1080元,实际成本仅为每瓶4元!" |
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} |
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``` |
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- "human_label" (`int`): the human-labeled summary quality score(Only the validation set and the test set have this label, and the data set only includes 3, 4, and 5 points data, not including 1, 2 points data.). |
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- "text" (`str`): input text. |
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- "summary"(`str`): a output summary. |
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### Evaluation Code |
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The prediction result needs to be consistent with the format of the evaluation code. |
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Dependency packages: rouge==1.0.0, jieba=0.42.1 |
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```shell |
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python eval.py prediction_file test_private_file |
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``` |
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The evaluation metrics are rouge-1, rouge-2, rouge-l, and the output is in dictionary format. |
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```she |
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return { |
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"rouge-1-f": _, |
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"rouge-1-p": _, |
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"rouge-1-r": _, |
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"rouge-2-f": _, |
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"rouge-2-p": _, |
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"rouge-2-r": _, |
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"rouge-l-f": _, |
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"rouge-l-p": _, |
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"rouge-l-r": _} |
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``` |
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### Author List |
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Baotian Hu, Qingcai Chen, Fangze Zhu |
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### Institutions |
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Harbin Institute of Technology |
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### Citation |
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``` |
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@inproceedings{hu2015lcsts, |
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title={LCSTS: A Large Scale Chinese Short Text Summarization Dataset}, |
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author={Hu, Baotian and Chen, Qingcai and Zhu, Fangze}, |
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booktitle={Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing}, |
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pages={1967--1972}, |
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year={2015} |
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} |
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``` |
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