https://github.com/ozgen/lstm-ner-ingredient

https://github.com/ozgen/lstm-ner-ingredient

bidirectional-lstm deep-learning ingredients keras lstm ner nlp-machine-learning part-of-speech-tagger python2

Last synced: about 1 month ago
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• Host: GitHub
• URL: https://github.com/ozgen/lstm-ner-ingredient
• Owner: ozgen
• Created: 2018-05-16T08:11:46.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2020-12-22T12:47:07.000Z (about 4 years ago)
• Last Synced: 2024-11-09T13:30:14.267Z (3 months ago)
• Topics: bidirectional-lstm, deep-learning, ingredients, keras, lstm, ner, nlp-machine-learning, part-of-speech-tagger, python2
• Language: Python
• Size: 23.5 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# LSTM_NER_Ingredient

# Ingredient Name Entity Recognition With Bidirectional LSTM Model

First of all, we use keras in order to implement

 * Inspiration for this project comes from ny-times working. You can reach from [here][nytimes].

 

 NOTE: Dataset will be added soon. If you want to get dataset asap, you can download [here][dataset]

[crf_tut]:  http://people.cs.umass.edu/~mccallum/papers/crf-tutorial.pdf

[nytimes]: https://github.com/NYTimes/ingredient-phrase-tagger

[dataset]: https://github.com/NYTimes/ingredient-phrase-tagger/blob/master/nyt-ingredients-snapshot-2015.csv