Named Entity Recognition
Showing 14 of 14 projects
TensorFlow implementation and pre-trained models for BERT, a bidirectional Transformer for language understanding.
Industrial-strength Natural Language Processing library for Python, featuring pretrained pipelines for 70+ languages and production-ready training.
A community-driven repository tracking datasets and state-of-the-art results for common NLP tasks across multiple languages.
A simple Python framework for state-of-the-art natural language processing (NLP) tasks like named entity recognition and sentiment analysis.
A simple Python framework for state-of-the-art natural language processing (NLP) tasks like named entity recognition and sentiment analysis.
A lightweight JavaScript library for natural language processing that transforms text into structured data with a modest, pragmatic approach.
A Python NLP library from Stanford for tokenization, sentence segmentation, NER, and dependency parsing across 60+ languages.
An open-source NLP framework for building and deploying deep learning dialog systems and chatbots with PyTorch and transformers.
A state-of-the-art Natural Language Processing library built on Apache Spark, offering 100,000+ pretrained models and pipelines in 200+ languages.
A free, state-of-the-art library and toolkit for named entity extraction and binary relation detection from text.
A web/desktop application for collaborative labeling and annotation of images, text, audio, documents, and other data types.
A spaCy pipeline and models specifically designed for processing scientific and biomedical documents.
An easy-to-use, state-of-the-art named-entity recognition (NER) tool based on neural networks.
A BERT language model pre-trained on a large corpus of scientific papers for natural language processing tasks in scientific domains.
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