Search Results for "metadata"
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Showing 7 open source projects for "metadata"
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1
Docspell
Assist in organizing your piles of documents
...This makes adding metadata to your documents a lot easier. For machine learning, it relies on the free (GPL) Stanford Core NLP library. -
2
PaperAI
Semantic search and workflows for medical/scientific papers
PaperAI is an open-source framework for searching and analyzing scientific papers, particularly useful for researchers looking to extract insights from large-scale document collections. -
3
deepdoctection
A Repo For Document AI
DeepDoctection is a document AI framework that applies deep learning techniques to analyze and extract structured data from scanned documents, PDFs, and images. deepdoctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated frameworks for... -
4
textacy
NLP, before and after spaCy
textacy is a Python library for performing a variety of natural language processing (NLP) tasks, built on the high-performance spaCy library. With the fundamentals, tokenization, part-of-speech tagging, dependency parsing, etc., delegated to another library, textacy focuses primarily on the tasks that come before and follow after. -
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5
Parsr
Transforms PDF, Documents and Images into Enriched Structured Data
Parsr is an open-source document parsing tool that converts PDFs, scanned images, and other structured documents into structured, machine-readable data formats. -
6
CC-Net
Tools to download and cleanup Common Crawl data
cc_net provides tools to download, segment, clean, and filter Common Crawl to build large-scale text corpora, including monolingual datasets and the multilingual CC-100 collection introduced in the associated paper. It includes pipelines to fetch snapshots, extract text, de-duplicate, identify language, and apply quality filtering based on heuristics and language models. The outputs are intended for pretraining language models and for creating standardized corpora that can be reproduced or... -
7
Semantic Assistants
Natural Language Processing (NLP) for the Masses
Semantic Assistants support users in content retrieval, analysis, and development, by offering context-sensitive NLP services directly integrated in standard desktop clients, like a word processor, and web information systems, like a wiki.
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