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
this https URL.

本文发布了第一个英文版的体育比赛摘要数据集 GOAL，其中包含了 103 组评论 - 新闻对和 2160 个未标记的评论文档，并基于该数据集建立和评估了几种基线模型，包括抽取式和生成式模型。实验结果表明该任务仍然具有挑战性，并且希望该工作能够促进体育比赛摘要的深入研究。

目标：朝着少样本体育比赛摘要基准测试的方向

GOAL: Towards Benchmarking Few-Shot Sports Game Summarization

Sports game summarization aims at generating sports news from live
commentaries. However, existing datasets are all constructed through automated
collection and cleaning processes, resulting in a lot of noise. Besides,
current works neglect the knowledge gap between live commentaries and sports
news, which limits the performance of sports game summarization. In this paper,
we introduce K-SportsSum, a new dataset with two characteristics: (1)
K-SportsSum collects a large amount of data from massive games. It has 7,854
commentary-news pairs. To improve the quality, K-SportsSum employs a manual
cleaning process; (2) Different from existing datasets, to narrow the knowledge
gap, K-SportsSum further provides a large-scale knowledge corpus that contains
the information of 523 sports teams and 14,724 sports players. Additionally, we
also introduce a knowledge-enhanced summarizer that utilizes both live
commentaries and the knowledge to generate sports news. Extensive experiments
on K-SportsSum and SportsSum datasets show that our model achieves new
state-of-the-art performances. Qualitative analysis and human study further
verify that our model generates more informative sports news.

本文介绍了 K-SportsSum，它是一个由大规模比赛实时评论和体育新闻构成的新数据集，并提出了一种知识增强式总结器，利用实时评论和知识来生成更具信息量的体育新闻，实验证明了我们的模型达到了新的最高水平。