Abstract
The lack of data for information extraction (IE) from semi-structured business documents is a real problem for the IE community. Publications relying on large-scale datasets use only proprietary, unpublished data due to the sensitive nature of such documents. Publicly available datasets are mostly small and domain-specific. The absence of a large-scale public dataset or benchmark hinders the reproducibility and cross-evaluation of published methods. The DocILE 2023 competition, hosted as a lab at the CLEF 2023 conference and as an ICDAR 2023 competition, will run the first major benchmark for the tasks of Key Information Localization and Extraction (KILE) and Line Item Recognition (LIR) from business documents. With thousands of annotated real documents from open sources, a hundred thousand of generated synthetic documents, and nearly a million unlabeled documents, the DocILE lab comes with the largest publicly available dataset for KILE and LIR. We are looking forward to contributions from the Computer Vision, Natural Language Processing, Information Retrieval, and other communities. The data, baselines, code and up-to-date information about the lab and competition are available at this https URL.
Abstract (translated)
信息抽取(IE)从半结构化商业文档的数据缺乏是一个真正的问题,依赖于大规模数据集的出版物仅使用 proprietary 且未公开的数据,因为这些文档的敏感性质。公开可用的数据大部分很小且特定领域。缺乏大规模公共数据集或基准妨碍了公开方法的重复性和交叉评估。 DocILE 2023 竞争,作为 CLEF 2023 会议实验室和ICDAR 2023 竞争的一部分,将运行关键信息定位和提取(KILE)和条目识别(LIR)任务的第一个主要基准。 DocILE 实验室拥有最大的公开可用 KILE 和 LIR 数据集。我们期待着计算机视觉、自然语言处理、信息检索和其他社区的贡献。数据和基线、代码和实验室和竞争的最新信息可在 this https URL 上获取。
URL
https://arxiv.org/abs/2301.12394
