@inproceedings{412045493b2d4943902a87841034c908,
title = "Dataset for the first evaluation on Chinese machine reading comprehension",
abstract = "Machine Reading Comprehension (MRC) has become enormously popular recently and has attracted a lot of attention. However, existing reading comprehension datasets are mostly in English. To add diversity in reading comprehension datasets, in this paper we propose a new Chinese reading comprehension dataset for accelerating related research in the community. The proposed dataset contains two different types: cloze-style reading comprehension and user query reading comprehension, associated with large-scale training data as well as human-annotated validation and hidden test set. Along with this dataset, we also hosted the first Evaluation on Chinese Machine Reading Comprehension (CMRC-2017) and successfully attracted tens of participants, which suggest the potential impact of this dataset.",
keywords = "Chinese reading comprehension, Evaluation, Question answering",
author = "Yiming Cui and Ting Liu and Zhipeng Chen and Wentao Ma and Shijin Wang and Guoping Hu",
note = "Publisher Copyright: {\textcopyright} LREC 2018 - 11th International Conference on Language Resources and Evaluation. All rights reserved.; 11th International Conference on Language Resources and Evaluation, LREC 2018 ; Conference date: 07-05-2018 Through 12-05-2018",
year = "2018",
language = "英语",
series = "LREC 2018 - 11th International Conference on Language Resources and Evaluation",
publisher = "European Language Resources Association (ELRA)",
pages = "2721--2725",
editor = "Nicoletta Calzolari and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Helene Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga",
booktitle = "LREC 2018 - 11th International Conference on Language Resources and Evaluation",
}