siddhant-savant/CulinaryNER
Named Entity Recognition for Culinary Text - Trained spaCy model for granular restaurant review analysis
This project helps restaurant owners, marketers, and food critics analyze UK restaurant reviews by automatically identifying key culinary details. It takes raw review text as input and outputs structured information such as dish names, ingredients, cooking techniques, flavors, textures, cuisines, and chef names. Anyone in the food and hospitality industry looking to understand customer feedback at a granular level would benefit from this tool.
Use this if you need to quickly extract specific culinary entities from a large volume of UK restaurant reviews to gain insights into menu performance, customer preferences, or chef reputation.
Not ideal if your reviews are not from the UK context or you require analysis for dietary restrictions or plating aesthetics, as these are not currently supported entities.
Stars
9
Forks
—
Language
Python
License
MIT
Category
Last pushed
Feb 19, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/siddhant-savant/CulinaryNER"
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...