GOAL: Towards Benchmarking Few-Shot Sports Game Summarization
- URL: http://arxiv.org/abs/2207.08635v1
- Date: Mon, 18 Jul 2022 14:29:18 GMT
- Title: GOAL: Towards Benchmarking Few-Shot Sports Game Summarization
- Authors: Jiaan Wang, Tingyi Zhang, Haoxiang Shi
- Abstract summary: We release GOAL, the first English sports game summarization dataset.
There are 103 commentary-news pairs in GOAL, where the average lengths of commentaries and news are 2724.9 and 476.3 words, respectively.
- Score: 0.3683202928838613
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Sports game summarization aims to generate sports news based on real-time
commentaries. The task has attracted wide research attention but is still
under-explored probably due to the lack of corresponding English datasets.
Therefore, in this paper, we release GOAL, the first English sports game
summarization dataset. Specifically, there are 103 commentary-news pairs in
GOAL, where the average lengths of commentaries and news are 2724.9 and 476.3
words, respectively. Moreover, to support the research in the semi-supervised
setting, GOAL additionally provides 2,160 unlabeled commentary documents. Based
on our GOAL, we build and evaluate several baselines, including extractive and
abstractive baselines. The experimental results show the challenges of this
task still remain. We hope our work could promote the research of sports game
summarization. The dataset has been released at
https://github.com/krystalan/goal.
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