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
Venues:
INLG | WS
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
523–528
Language:
URL:
https://aclanthology.org/W19-8666
DOI:
10.18653/v1/W19-8666
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/W19-8666.pdf