Towards Summarization for Social Media - Results of the TL;DR Challenge
Shahbaz Syed, Michael Völske, Nedim Lipka, Benno Stein, Hinrich Schütze, Martin Potthast
Abstract
In this paper, we report on the results of the TL;DR challenge, discussing an extensive manual evaluation of the expected properties of a good summary based on analyzing the comments provided by human annotators.- Anthology ID:
- W19-8666
- Volume:
- Proceedings of the 12th International Conference on Natural Language Generation
- Month:
- October–November
- Year:
- 2019
- Address:
- Tokyo, Japan
- Editors:
- Kees van Deemter, Chenghua Lin, Hiroya Takamura
- Venue:
- INLG
- SIG:
- SIGGEN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 523–528
- Language:
- URL:
- https://aclanthology.org/W19-8666
- DOI:
- 10.18653/v1/W19-8666
- Cite (ACL):
- Shahbaz Syed, Michael Völske, Nedim Lipka, Benno Stein, Hinrich Schütze, and Martin Potthast. 2019. Towards Summarization for Social Media - Results of the TL;DR Challenge. In Proceedings of the 12th International Conference on Natural Language Generation, pages 523–528, Tokyo, Japan. Association for Computational Linguistics.
- Cite (Informal):
- Towards Summarization for Social Media - Results of the TL;DR Challenge (Syed et al., INLG 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/W19-8666.pdf