论文标题
YASO：针对开放域评论的目标情感分析评估数据集
YASO: A Targeted Sentiment Analysis Evaluation Dataset for Open-Domain Reviews
论文作者
论文摘要
跨域设置中的当前TSA评估仅限于现有数据集中可用的少量评论域。这样的评估是有限的，并且可能不会反映在亚马逊或Yelp等网站上的真实表现，这些网站是来自许多领域的各种评论。为了解决此差距，我们提出YASO-开放域用户评论的新的TSA评估数据集。 Yaso包含来自数十个审查领域的2,215个英语句子，并带有目标条款及其情感。我们的分析验证了这些注释的可靠性，并探讨了收集数据的特征。使用五个当代TSA系统的基准结果表明，在这个具有挑战性的新数据集上有足够的改进空间。 Yaso可从https://github.com/ibm/yaso-tsa获得。
Current TSA evaluation in a cross-domain setup is restricted to the small set of review domains available in existing datasets. Such an evaluation is limited, and may not reflect true performance on sites like Amazon or Yelp that host diverse reviews from many domains. To address this gap, we present YASO - a new TSA evaluation dataset of open-domain user reviews. YASO contains 2,215 English sentences from dozens of review domains, annotated with target terms and their sentiment. Our analysis verifies the reliability of these annotations, and explores the characteristics of the collected data. Benchmark results using five contemporary TSA systems show there is ample room for improvement on this challenging new dataset. YASO is available at https://github.com/IBM/yaso-tsa.
