

# 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
```

task_categories:token-classification task_ids:named-entity-recognition annotations_creators:expert-generated language_creators:found multilinguality:monolingual size_categories:100K<n<1M language:en license:apache-2.0 recipe ingredients region:us
{"annotations_creators": ["expert-generated"], "language_creators": ["found"], "language": ["en"], "license": ["apache-2.0"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": [], "task_categories": ["token-classification"], "task_ids": ["named-entity-recognition"], "pretty_name": "nyt_ingredients", "tags": ["recipe", "ingredients"]}
TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #language-English #license-apache-2.0 #recipe #ingredients #region-us 



# New York Times Ingredient Phrase Tagger Dataset

Original source: URL

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.
> 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:



# New York Times Ingredient Phrase Tagger Dataset

Original source: URL

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.
> 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:
TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #language-English #license-apache-2.0 #recipe #ingredients #region-us 
 # New York Times Ingredient Phrase Tagger Dataset

Original source: URL

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.
> 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: