The timeline generation task summarises an entity's biography by selecting stories representing key events from a large pool of relevant documents. This paper addresses the lack of a standard dataset and evaluative methodology for the problem. We present and make publicly available a new dataset of 18,793 news articles covering 39 entities. For each entity, we provide a gold standard timeline and a set of entity-related articles. We propose ROUGE as an evaluation metric and validate our dataset by showing that top Google results outperform straw-man baselines.
@article{arxiv.1611.02025,
title = {Presenting a New Dataset for the Timeline Generation Problem},
author = {Xavier Holt and Will Radford and Ben Hachey},
journal= {arXiv preprint arXiv:1611.02025},
year = {2016}
}