stevezheng23/sequence_labeling_tf
Sequence Labeling in Tensorflow
This tool helps you automatically categorize individual words or phrases within a sequence of text, such as identifying all the people's names or locations in a document. You provide text data, and it outputs the same text with labels attached to specific parts. This is for data scientists or NLP engineers who build custom natural language processing solutions.
No commits in the last 6 months.
Use this if you need to assign specific labels to elements within a sequence, like tagging parts of speech or extracting named entities from large text datasets.
Not ideal if you're looking for an out-of-the-box solution with a graphical interface or if you don't have experience with Python and TensorFlow.
Stars
18
Forks
1
Language
Python
License
Apache-2.0
Category
Last pushed
Jun 12, 2019
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/stevezheng23/sequence_labeling_tf"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
chakki-works/seqeval
A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)
Hironsan/anago
Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-Speech Tagging and so on.
jbesomi/texthero
Text preprocessing, representation and visualization from zero to hero.
hamelsmu/ktext
Utilities for preprocessing text for deep learning with Keras
asahi417/tner
Language model fine-tuning on NER with an easy interface and cross-domain evaluation. "T-NER: An...