kamalkraj/Named-Entity-Recognition-with-Bidirectional-LSTM-CNNs
Named-Entity-Recognition-with-Bidirectional-LSTM-CNNs
This project helps developers build systems that can automatically identify and categorize key information like names of people, organizations, or locations within text. You feed it raw text, and it outputs the text with specific words or phrases tagged with their entity type. This is primarily useful for developers creating natural language processing applications or data extraction tools.
369 stars. No commits in the last 6 months.
Use this if you are a developer looking for a Keras-based implementation to perform Named Entity Recognition on text data.
Not ideal if you need an out-of-the-box solution for end-users, or if you require a pre-trained model ready for immediate use without development.
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369
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142
Language
Python
License
GPL-3.0
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Last pushed
Apr 21, 2020
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