Abstract
Sentence ordering is the task of arranging the sentences of a given text in the correct order. Recent work using deep neural networks for this task has framed it as a sequence prediction problem. In this paper, we propose a new framing of this task as a constraint solving problem and introduce a new technique to solve it. Additionally, we propose a human evaluation for this task. The results on both automatic and human metrics across four different datasets show that this new technique is better at capturing coherence in documents.- Anthology ID:
- 2020.acl-main.248
- Volume:
- Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2020
- Address:
- Online
- Editors:
- Dan Jurafsky, Joyce Chai, Natalie Schluter, Joel Tetreault
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2783–2792
- Language:
- URL:
- https://aclanthology.org/2020.acl-main.248
- DOI:
- 10.18653/v1/2020.acl-main.248
- Cite (ACL):
- Shrimai Prabhumoye, Ruslan Salakhutdinov, and Alan W Black. 2020. Topological Sort for Sentence Ordering. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 2783–2792, Online. Association for Computational Linguistics.
- Cite (Informal):
- Topological Sort for Sentence Ordering (Prabhumoye et al., ACL 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2020.acl-main.248.pdf
- Code
- shrimai/Topological-Sort-for-Sentence-Ordering + additional community code