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GROBID
GROBID is a machine learning software for extracting information from scholarly documents into structured formats.
GROBID is a machine learning library designed for extracting, parsing, and re-structuring raw documents like PDFs into structured XML or TEI encoded documents, with a strong focus on technical and scientific publications. It handles header extraction, reference parsing, citation context recognition, full text structuring, and PDF coordinate mapping. The software uses deep learning models via JEP or default feature-engineered CRFs to balance speed and accuracy. It is built for researchers, developers, and organizations working with large corpora of scholarly literature. GROBID provides a web service API, Java API, Docker images, batch processing, and client libraries in Python, Java, Node.js, and Go.
GROBID at a glance
- Best for: Researcher
- Runs on: Linux, macOS, API, self-hosted, open source
- Pricing: Free
- Released: September 2012
- Category: AI research tool
- Website: github.com/grobidOrg/grobid
Key features
- Header extraction and parsing
- References extraction and parsing
- Citation contexts recognition
- Full text extraction and structuring
- PDF coordinates for extracted information
- Parsing of names and affiliations
- Consolidation of bibliographical references
Use it for
- Extracting metadata from academic papers
- Parsing bibliographical references from PDFs
- Structuring full text scientific articles
- Processing large corpora of scholarly literature
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