WikiSum: Coherent Summarization Dataset for Efficient Human-Evaluation
Nachshon Cohen, Oren Kalinsky, Yftah Ziser, Alessandro Moschitti
Abstract
Recent works made significant advances on summarization tasks, facilitated by summarization datasets. Several existing datasets have the form of coherent-paragraph summaries. However, these datasets were curated from academic documents that were written for experts, thus making the essential step of assessing the summarization output through human-evaluation very demanding. To overcome these limitations, we present a dataset based on article summaries appearing on the WikiHow website, composed of how-to articles and coherent-paragraph summaries written in plain language. We compare our dataset attributes to existing ones, including readability and world-knowledge, showing our dataset makes human evaluation significantly easier and thus, more effective. A human evaluation conducted on PubMed and the proposed dataset reinforces our findings.- Anthology ID:
- 2021.acl-short.28
- Volume:
- Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
- Month:
- August
- Year:
- 2021
- Address:
- Online
- Editors:
- Chengqing Zong, Fei Xia, Wenjie Li, Roberto Navigli
- Venues:
- ACL | IJCNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 212–219
- Language:
- URL:
- https://aclanthology.org/2021.acl-short.28
- DOI:
- 10.18653/v1/2021.acl-short.28
- Cite (ACL):
- Nachshon Cohen, Oren Kalinsky, Yftah Ziser, and Alessandro Moschitti. 2021. WikiSum: Coherent Summarization Dataset for Efficient Human-Evaluation. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pages 212–219, Online. Association for Computational Linguistics.
- Cite (Informal):
- WikiSum: Coherent Summarization Dataset for Efficient Human-Evaluation (Cohen et al., ACL-IJCNLP 2021)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2021.acl-short.28.pdf
- Data
- BigPatent, OpenSubtitles, WikiHow