Extract bibliographic data from PDFs
This space contains 4 usecases in Law Domain.
Generate documentation for Hugging Face spaces
Search ECCV 2022 papers by title
Generate vehicle CO2 report
Generate a profile report for a dataset
Parse document layouts from images
Display interactive PDF documents
Extract bibliographical information from PDFs
Analyze documents to extract text and visualize segmentation
Run text analysis on your documents
Display blog posts with summaries
Search for articles using Hindi keywords
Grobid is a machine learning-based tool designed for extracting bibliographic data from PDF documents. It automatically identifies and parses structured information such as titles, authors, references, and more, making it a powerful resource for document analysis and academic workflows.
• Bibliographic Data Extraction: Accurately extracts metadata like title, authors, publication venue, and dates from PDFs.
• Reference Parsing: Identifies and extracts references from academic papers, supporting multiple citation styles.
• Document Segmentation: Recognizes sections like abstracts, keywords, and conclusions within documents.
• Multilingual Support:Processes documents in multiple languages, expanding its utility across global research.
• Open Source: Freely available for use, customization, and integration into other applications.
• High Accuracy: Leverages advanced machine learning models to ensure precise data extraction.
docker run -d --name grobid -p 8070:8070 grobid/grobid
What file formats does Grobid support?
Grobid primarily works with PDF documents, but it can also process other text-based formats to some extent.
Can Grobid handle handwritten or scanned PDFs?
Grobid performs best with machine-readable PDFs. Scanned or handwritten documents may require OCR (Optical Character Recognition) preprocessing for accurate results.
Is Grobid free to use?
Yes, Grobid is open-source and free to use, making it accessible for academic and research purposes.