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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},
      booktitle = {EMNLP},
      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

    Mingyu Derek Ma, Jiao Sun, Mu Yang, Kung-Hsiang Huang, Nuan Wen, Shikhar Singh, Rujun Han, and Nanyun Peng, in 2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), Demonstrations Track, 2021.
    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},
      year = {2021}
    }
    
    Details