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ReCAM: Reading Comprehension of Abstract Meaning
Table of Contents
- Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
This dataset is from SemEval 2021 Task 4: Reading Comprehension of Abstract Meaning. Original repository for the dataset and baseline code can be accessed here.
- Paper: SemEval-2021 Task 4: Reading Comprehension of Abstract Meaning in ACL
- Leaderboard: CodaLab
Dataset Summary
Refer to this page.
Dataset Structure
Refer to the GitHub.
Data Instances
[More Information Needed]
Data Fields
[More Information Needed]
Data Splits
[More Information Needed]
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
[More Information Needed]
Licensing Information
[More Information Needed]
Citation Information
@inproceedings{zheng-etal-2021-semeval,
title = "{S}em{E}val-2021 Task 4: Reading Comprehension of Abstract Meaning",
author = "Zheng, Boyuan and
Yang, Xiaoyu and
Ruan, Yu-Ping and
Ling, Zhenhua and
Liu, Quan and
Wei, Si and
Zhu, Xiaodan",
booktitle = "Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.semeval-1.4",
doi = "10.18653/v1/2021.semeval-1.4",
pages = "37--50",
}
Contributions
Thanks to @github-username for adding this dataset.