Abstract
We introduce a new Information Extraction (IE) task dubbed Instruction-based IE, which aims to ask the system to follow specific instructions or guidelines to extract information. To facilitate research in this area, we construct a dataset called InstructIE, consisting of 270,000 weakly supervised data from Chinese Wikipedia and 1,000 high-quality crowdsourced annotated instances. We further evaluate the performance of various baseline models on the InstructIE dataset. The results reveal that although current models exhibit promising performance, there is still room for improvement. Furthermore, we conduct a comprehensive case study analysis, underlining the challenges inherent in the Instruction-based IE task. Code and dataset are available at this https URL.
Abstract (translated)
我们介绍了一个名为“基于指示的信息提取”的新任务，该任务旨在要求系统遵循特定的指示或指南来提取信息。为了促进该领域的研究，我们建立了一个名为“指示IE”的数据集，该数据集由270,000条弱监督数据从中国维基百科中提取，以及1,000条高质量的 crowdsourced 注释实例组成。我们还对该数据集的各种基线模型的性能进行了评估。结果显示，尽管当前模型表现出良好的性能，但仍有改进的空间。此外，我们进行了全面的案例分析，突出了基于指示的信息提取任务固有的挑战。代码和数据集可在这个httpsURL上获取。
URL
https://arxiv.org/abs/2305.11527
