Enumerate all ner_tags values in WNUT 17 dataset

datasets/wnut_17/README.md

@@ -1,7 +1,24 @@
 ---
+annotations_creators:
+- crowdsourced
+language_creators:
+- found
 languages:
 - en
+licenses:
+- cc-by-4.0
+multilinguality:
+- monolingual
 paperswithcode_id: wnut-2017-emerging-and-rare-entity
+pretty_name: WNUT 17
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- structure-prediction
+task_ids:
+- named-entity-recognition
 ---
 
 # Dataset Card for "wnut_17"
@@ -62,12 +79,8 @@ The goal of this task is to provide a definition of emerging and of rare entitie
 
 ## Dataset Structure
 
-We show detailed information for up to 5 configurations of the dataset.
-
 ### Data Instances
 
-#### wnut_17
-
 - **Size of downloaded dataset files:** 0.76 MB
 - **Size of the generated dataset:** 1.66 MB
 - **Total amount of disk used:** 2.43 MB
@@ -83,18 +96,29 @@ An example of 'train' looks as follows.
 
 ### Data Fields
 
-The data fields are the same among all splits.
-
-#### wnut_17
-- `id`: a `string` feature.
-- `tokens`: a `list` of `string` features.
-- `ner_tags`: a `list` of classification labels, with possible values including `O` (0), `B-corporation` (1), `I-corporation` (2), `B-creative-work` (3), `I-creative-work` (4).
+The data fields are the same among all splits:
+- `id` (`string`): ID of the example.
+- `tokens` (`list` of `string`): Tokens of the example text.
+- `ner_tags` (`list` of class labels): NER tags of the tokens (using IOB2 format), with possible values:
+  - 0: `O`
+  - 1: `B-corporation`
+  - 2: `I-corporation`
+  - 3: `B-creative-work`
+  - 4: `I-creative-work`
+  - 5: `B-group`
+  - 6: `I-group`
+  - 7: `B-location`
+  - 8: `I-location`
+  - 9: `B-person`
+  - 10: `I-person`
+  - 11: `B-product`
+  - 12: `I-product`
 
 ### Data Splits
 
-| name  |train|validation|test|
-|-------|----:|---------:|---:|
-|wnut_17| 3394|      1009|1287|
+|train|validation|test|
+|----:|---------:|---:|
+| 3394|      1009|1287|
 
 ## Dataset Creation