Datasets:
Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
100K<n<1M
License:
annotations_creators: | |
- expert-generated | |
language: | |
- en | |
language_creators: | |
- found | |
license: | |
- apache-2.0 | |
multilinguality: | |
- monolingual | |
pretty_name: nyt_ingredients | |
size_categories: | |
- 100K<n<1M | |
source_datasets: [] | |
tags: | |
- recipe | |
- ingredients | |
task_categories: | |
- token-classification | |
task_ids: | |
- named-entity-recognition | |
# New York Times Ingredient Phrase Tagger Dataset | |
Original source: https://github.com/nytimes/ingredient-phrase-tagger | |
From the source: | |
> We use a conditional random field model (CRF) to extract tags from labelled training data, which was tagged by human news assistants. | |
> We wrote about our approach on the [New York Times Open blog](http://open.blogs.nytimes.com/2015/04/09/extracting-structured-data-from-recipes-using-conditional-random-fields/). | |
> This repo contains scripts to extract the Quantity, Unit, Name, and Comments from unstructured ingredient phrases. | |
> We use it on Cooking to format incoming recipes. Given the following input: | |
``` | |
1 pound carrots, young ones if possible | |
Kosher salt, to taste | |
2 tablespoons sherry vinegar | |
2 tablespoons honey | |
2 tablespoons extra-virgin olive oil | |
1 medium-size shallot, peeled and finely diced | |
1/2 teaspoon fresh thyme leaves, finely chopped | |
Black pepper, to taste | |
``` | |