saiwaiyanyu/bi-lstm-crf-ner-tf2.0
Named Entity Recognition (NER) task using Bi-LSTM-CRF model implemented in Tensorflow 2.0(tensorflow2.0 +)
This tool helps you automatically identify and classify key pieces of information, like names of people, organizations, locations, and dates, within raw text documents. You provide a dataset of text where these entities are already labeled, and it produces a trained model that can then extract similar entities from new, unseen text. It's designed for data scientists or NLP engineers who need to build custom named entity recognition systems for specific domains or languages.
120 stars. No commits in the last 6 months.
Use this if you need to build a specialized model to extract specific types of entities from unstructured text data, and you have labeled examples to train it.
Not ideal if you need an out-of-the-box solution for common entity types without custom training, or if you don't have a labeled dataset.
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Python
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Last pushed
Jun 05, 2020
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