jiesutd/NCRFpp
NCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.
This project helps you automatically categorize words and phrases within text, like identifying all person names or locations in a document, or tagging parts of speech. You provide text data with examples of how words should be labeled, and it produces a system that can accurately tag new, unseen text. It's ideal for data scientists or researchers who need to perform highly accurate text analysis for tasks like information extraction or text structuring.
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Use this if you need to precisely label sequences of words in text, such as for Named Entity Recognition (NER), part-of-speech tagging, or word segmentation, and want a high-performance solution without writing complex code.
Not ideal if you're looking for a simple keyword extraction tool or a full natural language understanding pipeline that includes components beyond sequence labeling.
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Python
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Apache-2.0
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Last pushed
Jun 30, 2022
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