arXiv · 2101.10281
PAWLS: PDF Annotation With Labels and Structure
Abstract
Adobe's Portable Document Format (PDF) is a popular way of distributing view-only documents with a rich visual markup. This presents a challenge to NLP practitioners who wish to use the information contained within PDF documents for training models or data analysis, because annotating these documents is difficult. In this paper, we present PDF Annotation with Labels and Structure (PAWLS), a new annotation tool designed specifically for the PDF document format. PAWLS is particularly suited for mixed-mode annotation and scenarios in which annotators require extended context to annotate accurately. PAWLS supports span-based textual annotation, N-ary relations and freeform, non-textual bounding boxes, all of which can be exported in convenient formats for training multi-modal machine learning models. A read-only PAWLS server is available at https://pawls.apps.allenai.org/ and the source code is available at https://github.com/allenai/pawls.
Explore related subjects
Keep this discovery
Mark Neumann, Zejiang Shen, Sam Skjonsberg. 2021-01-25. PAWLS: PDF Annotation With Labels and Structure. https://arxiv.org/abs/2101.10281
Cite the original work for its findings. Save a collection to share your selection of sources.