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ESTER: A Machine Reading Comprehension Dataset for Event Semantic Relation Reasoning

Rujun Han, I.-Hung Hsu, Jiao Sun, Julia Baylon, Qiang Ning, Dan Roth, and Nanyun Peng, in EMNLP, 2021.

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@inproceedings{han2021ester,
  title = {ESTER: A Machine Reading Comprehension Dataset for Event Semantic Relation Reasoning},
  author = {Han, Rujun and Hsu, I-Hung and Sun, Jiao and Baylon, Julia and Ning, Qiang and Roth, Dan and Peng, Nanyun},
  booktitle = {EMNLP},
  presentation_id = {https://underline.io/events/192/sessions/7816/lecture/37869-ester-a-machine-reading-comprehension-dataset-for-reasoning-about-event-semantic-relations},
  year = {2021}
}

Related Publications

  1. ESTER: A Machine Reading Comprehension Dataset for Event Semantic Relation Reasoning

    Rujun Han, I.-Hung Hsu, Jiao Sun, Julia Baylon, Qiang Ning, Dan Roth, and Nanyun Peng, in EMNLP, 2021.
    Full Text Code BibTeX Details 
    @inproceedings{han2021ester,
  title = {ESTER: A Machine Reading Comprehension Dataset for Event Semantic Relation Reasoning},
  author = {Han, Rujun and Hsu, I-Hung and Sun, Jiao and Baylon, Julia and Ning, Qiang and Roth, Dan and Peng, Nanyun},
  booktitle = {EMNLP},
  presentation_id = {https://underline.io/events/192/sessions/7816/lecture/37869-ester-a-machine-reading-comprehension-dataset-for-reasoning-about-event-semantic-relations},
  year = {2021}
}
    Details

  2. ECONET: Effective Continual Pretraining of Language Models for Event Temporal Reasoning

    Rujun Han, Xiang Ren, and Nanyun Peng, in EMNLP, 2021.
    Full Text Code BibTeX Details 
    @inproceedings{han2021econet,
  title = {ECONET: Effective Continual Pretraining of Language Models for Event Temporal Reasoning},
  author = {Han, Rujun and Ren, Xiang and Peng, Nanyun},
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  presentation_id = {https://underline.io/events/192/posters/8243/poster/37875-econet-effective-continual-pretraining-of-language-models-for-event-temporal-reasoning},
  year = {2021}
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  3. EventPlus: A Temporal Event Understanding Pipeline

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    Full Text Slides Poster Video Code Abstract BibTeX Details 
    We present EventPlus, a temporal event understanding pipeline that integrates various state-of-the-art event understanding components including event trigger and type detection, event argument detection, event duration and temporal relation extraction. Event information, especially event temporal knowledge, is a type of common sense knowledge that helps people understand how stories evolve and provides predictive hints for future events. EventPlus as the first comprehensive temporal event understanding pipeline provides a convenient tool for users to quickly obtain annotations about events and their temporal information for any user-provided document. Furthermore, we show EventPlus can be easily adapted to other domains (e.g., biomedical domain). We make EventPlus publicly available to facilitate event-related information extraction and downstream applications.
    @inproceedings{ma2021eventplus,
  title = {EventPlus: A Temporal Event Understanding Pipeline},
  author = {Ma, Mingyu Derek and Sun, Jiao and Yang, Mu and Huang, Kung-Hsiang and Wen, Nuan and Singh, Shikhar and Han, Rujun and Peng, Nanyun},
  booktitle = {2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), Demonstrations Track},
  presentation_id = {https://underline.io/events/122/posters/4227/poster/20582-eventplus-a-temporal-event-understanding-pipeline},
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