sequence_tagging and tf_ner
About sequence_tagging
guillaumegenthial/sequence_tagging
Named Entity Recognition (LSTM + CRF) - Tensorflow
This tool helps you automatically identify and tag specific types of information in text, such as names of people, organizations, or locations. You provide sentences as input, and it outputs each word with a corresponding tag indicating if it's part of a named entity. It's designed for data scientists, linguists, or anyone who needs to extract structured information from unstructured text.
About tf_ner
guillaumegenthial/tf_ner
Simple and Efficient Tensorflow implementations of NER models with tf.estimator and tf.data
This project helps natural language processing engineers quickly implement and test state-of-the-art Named Entity Recognition (NER) models. You provide text sentences and corresponding tags, and the system outputs a trained model that can identify entities like names, locations, and organizations in new text. It is designed for NLP researchers and practitioners who need accurate and efficient entity extraction.
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