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on large-scale datasets use only proprietary, unpublished data due to the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.

该研究提供了一个大规模的公开数据集：DocILE，用于从半结构化商业文件中提取关键信息和识别项目行。该数据集将用于业界的基准测试，并鼓励计算机视觉、自然语言处理和信息检索等领域的贡献。