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Grobid is an open-source tool designed to extract bibliographical metadata from unstructured documents, particularly PDFs. It specializes in identifying and structuring information such as authors, titles, publication venues, and more. Grobid is widely used in text analysis, academic research, and document processing applications.
• Metadata Extraction: Extracts authors, titles, publication dates, venues, and URLs from PDFs.
• Reference Parsing: Identifies and structures citations and references within documents.
• Document Type Handling: Supports multiple document formats, including PDF, XML, and TXT.
• Customizable Output: Allows users to specify output formats such as JSON, XML, or CSV.
• API Integration: Provides RESTful APIs for seamless integration with other tools and workflows.
• High Accuracy: Leverages advanced machine learning models for precise metadata extraction.
• Fast Processing: Capable of handling large volumes of documents efficiently.
Example command to process a PDF:
curl -X POST -F "file=@your_document.pdf" http://localhost:8070/api/processFulltext
What types of documents does Grobid support?
Grobid primarily supports PDFs but can also process XML and TXT files.
How accurate is Grobid's metadata extraction?
Grobid achieves high accuracy due to its advanced machine learning models, but results may vary based on document quality and formatting.
Can Grobid integrate with other tools or workflows?
Yes, Grobid offers RESTful APIs, making it easy to integrate with other systems, libraries, or custom applications.