tianlinyang/stack-lstm-ner
Transition-based NER system
This project helps you automatically identify and tag specific entities like names of people, organizations, or locations within a sentence. You provide plain text sentences, and it outputs each word with its corresponding tag (e.g., "John" as a Person, "New York" as a Location). This tool is for anyone who needs to extract structured information from unstructured text, such as researchers analyzing documents or data scientists building text processing pipelines.
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Use this if you need to reliably categorize individual words or phrases in large volumes of text into predefined entity types.
Not ideal if you need to perform more complex text understanding tasks like sentiment analysis or question answering, which go beyond simple entity extraction.
Stars
35
Forks
11
Language
Python
License
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Last pushed
Jun 22, 2018
Commits (30d)
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