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Document Analysis
Grobid

Grobid

Extract bibliographic data from PDFs

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What is Grobid ?

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.

Features

• 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.

How to use Grobid ?

  1. Install Grobid: Download and install Grobid using Docker or by compiling the source code.
    docker run -d --name grobid -p 8070:8070 grobid/grobid
    
  2. Upload a PDF: Use the Grobid web interface or API to upload a PDF file for processing.
  3. Process the Document: Grobid analyzes the PDF and extracts bibliographic data in formats like JSON or TEI.
  4. Access Results: Retrieve the extracted data via the API or download it from the interface for further use.

Frequently Asked Questions

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.

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