shengc/tf-lstm-crf-tagger
TensorFlow Implementation For [Neural Architecture for Named Entity Recognition](https://arxiv.org/abs/1603.01360)
This tool helps data scientists and NLP engineers build models that can automatically identify and categorize specific entities within text, such as names of people, organizations, or locations. You provide raw text data, and it outputs a sequence of identified and labeled entities. It's designed for those who need to extract structured information from unstructured text efficiently.
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Use this if you need a robust way to automatically find and classify named entities in large volumes of text using a TensorFlow-based solution.
Not ideal if you require mini-batch processing for training, as this implementation currently processes sequences one by one.
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Apache-2.0
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Last pushed
Mar 04, 2018
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