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 | |
| ``` | |