SNUDerek/NER_bLSTM-CRF
LSTM-CRF for NER with ConLL-2002 dataset
This project helps you automatically identify and classify key entities like people, organizations, locations, and dates within written text, even if the text doesn't contain capitalization (like speech-to-text transcripts). You input raw text, and it outputs the same text with specific words and phrases tagged with their entity type. This is useful for anyone who needs to extract structured information from unstructured text, especially from sources where case information is missing.
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Use this if you need to reliably extract named entities from large volumes of text, particularly from sources like automatic speech recognition output where capitalization cues are absent.
Not ideal if your primary goal is to perform general text classification or sentiment analysis, rather than specifically identifying named entities.
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Jun 11, 2018
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