Card: en + multilingual, two million rows

README.md

@@ -1,6 +1,7 @@
 ---
 pretty_name: tasksource-jev-typed-decisions
 language:
+- en
 - multilingual
 license: other
 task_categories:
@@ -16,56 +17,11 @@ tags:
 - multiple-choice
 size_categories:
 - 1M<n<10M
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: validation
-    path: data/validation-*
-  - split: test
-    path: data/test-*
-dataset_info:
-  features:
-  - name: state
-    dtype: string
-  - name: kind
-    dtype: string
-  - name: id
-    dtype: string
-  - name: options
-    list: string
-  - name: target
-    list: float64
-  - name: question
-    dtype: string
-  - name: source
-    dtype: string
-  - name: variant
-    dtype: string
-  - name: split
-    dtype: string
-  - name: group_id
-    dtype: string
-  - name: question_id
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 2276576785
-    num_examples: 2000000
-  - name: validation
-    num_bytes: 16988434
-    num_examples: 15000
-  - name: test
-    num_bytes: 16858704
-    num_examples: 15000
-  download_size: 1315912356
-  dataset_size: 2310423923
 ---
 
 # tasksource-jev-typed-decisions
 
-**One million human-labeled decisions from 500+ tasks, in one format for models
+**Two million human-labeled decisions from 600+ tasks, in one format for models
 that read their answer criteria at runtime.**
 
 Most instruction data teaches a model to *write*. This dataset teaches it to
@@ -124,7 +80,7 @@ print(row["state"], row["question"], row["options"], row["target"])
 | `id`, `group_id`, `question_id` | Link decisions over the same source example |
 | `source`, `split`, `variant` | Originating task, original split, and recast variant |
 
-Splits: 1,000,000 train, 15,000 validation (`dev` in `split`), and 15,000 test,
+Splits: 2,000,000 train, 15,000 validation (`dev` in `split`), and 15,000 test,
 following each source's own train/dev/test splits where it has them.
 
 ## How it is built