26hzhang/neural_sequence_labeling
A TensorFlow implementation of Neural Sequence Labeling model, which is able to tackle sequence labeling tasks such as POS Tagging, Chunking, NER, Punctuation Restoration and etc.
This project helps people who work with text data to automatically understand and categorize parts of sentences. You input raw text, and it outputs the same text with labels assigned to each word or phrase, indicating things like parts of speech, named entities (like organizations or locations), or sentence boundaries. This is useful for linguists, data scientists, or anyone needing to structure and analyze large volumes of unstructured text.
233 stars. No commits in the last 6 months.
Use this if you need to extract specific information from text, categorize words, or prepare text for further analysis, like identifying all product names in customer reviews.
Not ideal if you're looking for a simple keyword search tool or if your main goal is text summarization rather than detailed word-level annotation.
Stars
233
Forks
46
Language
Python
License
MIT
Category
Last pushed
Nov 27, 2018
Commits (30d)
0
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