Fritz449/ProtoNER
Few-shot classification in Named Entity Recognition Task
ProtoNER helps you identify specific entities, like names or locations, within text documents when you only have a few examples of what those entities look like. You provide a small set of labeled text examples, and the system learns to find similar entities in new, unlabeled text. This is useful for researchers or data scientists who need to extract structured information from domain-specific texts without extensive manual labeling.
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Use this if you need to automatically extract specific types of information (named entities) from text, but you have very little pre-labeled data for your particular domain or entity types.
Not ideal if you already have large, well-labeled datasets for your named entity recognition task, or if you need a solution that doesn't require programming knowledge to implement.
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Language
Python
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Last pushed
Dec 18, 2018
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