Extract relations and perform NER from text
Multimodal retrieval using llamaindex/vdr-2b-multi-v1
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GLiREL is an advanced AI-powered tool designed to extract text from scanned documents while also performing Named Entity Recognition (NER) and relation extraction. It helps users unlock insights from unstructured data by identifying and categorizing entities and their relationships within the text. GLiREL is particularly useful for processing scanned documents, PDFs, and other image-based texts.
• Text Extraction: Accurately extracts text from scanned documents and images.
• Named Entity Recognition (NER): Identifies and categorizes entities such as names, locations, organizations, and dates.
• Relation Extraction: Detects relationships between identified entities.
• Multi-Format Support: Works with various document formats, including PDF, JPEG, PNG, and more.
• OCR Capability: Includes optical character recognition to handle scanned or handwritten text.
• Customizable Options: Users can fine-tune settings for specific use cases.
• High Accuracy: Leverages state-of-the-art AI models for precise results.
• Scalability: Suitable for small-scale and large-volume document processing.
What file formats does GLiREL support?
GLiREL supports a wide range of formats, including PDF, JPEG, PNG, BMP, and TIFF.
Can GLiREL handle documents with poor image quality?
Yes, GLiREL includes OCR capabilities to process scanned documents, even those with lower image quality. However, results may vary based on the clarity of the input.
How accurate is GLiREL in extracting relationships?
GLiREL leverages advanced AI models to achieve high accuracy in relation extraction. However, accuracy can depend on the quality of the input text and the complexity of the relationships.