Update README.md

README.md

@@ -1,707 +1,884 @@
----
-license: apache-2.0
-configs:
-- config_name: dataset_da_huse_2x3_5rh
-  data_files:
-  - split: train
-    path: dataset_da_huse_2x3_5rh/train-*
-  - split: test
-    path: dataset_da_huse_2x3_5rh/test-*
-- config_name: dataset_da_huse_4x5_5rh
-  data_files:
-  - split: train
-    path: dataset_da_huse_4x5_5rh/train-*
-  - split: test
-    path: dataset_da_huse_4x5_5rh/test-*
-- config_name: dataset_da_smoerrebroed_2x3_5rh
-  data_files:
-  - split: train
-    path: dataset_da_smoerrebroed_2x3_5rh/train-*
-  - split: test
-    path: dataset_da_smoerrebroed_2x3_5rh/test-*
-- config_name: dataset_da_smoerrebroed_4x5_5rh
-  data_files:
-  - split: train
-    path: dataset_da_smoerrebroed_4x5_5rh/train-*
-  - split: test
-    path: dataset_da_smoerrebroed_4x5_5rh/test-*
-- config_name: dataset_de_hauser_2x3_5rh
-  data_files:
-  - split: train
-    path: dataset_de_hauser_2x3_5rh/train-*
-  - split: test
-    path: dataset_de_hauser_2x3_5rh/test-*
-- config_name: dataset_de_hauser_4x5_5rh
-  data_files:
-  - split: train
-    path: dataset_de_hauser_4x5_5rh/train-*
-  - split: test
-    path: dataset_de_hauser_4x5_5rh/test-*
-- config_name: dataset_en_houses_2x3_5rh
-  data_files:
-  - split: train
-    path: dataset_en_houses_2x3_5rh/train-*
-  - split: test
-    path: dataset_en_houses_2x3_5rh/test-*
-- config_name: dataset_en_houses_4x5_5rh
-  data_files:
-  - split: train
-    path: dataset_en_houses_4x5_5rh/train-*
-  - split: test
-    path: dataset_en_houses_4x5_5rh/test-*
-- config_name: dataset_fo_hus_2x3_5rh
-  data_files:
-  - split: train
-    path: dataset_fo_hus_2x3_5rh/train-*
-  - split: test
-    path: dataset_fo_hus_2x3_5rh/test-*
-- config_name: dataset_fo_hus_4x5_5rh
-  data_files:
-  - split: train
-    path: dataset_fo_hus_4x5_5rh/train-*
-  - split: test
-    path: dataset_fo_hus_4x5_5rh/test-*
-- config_name: dataset_is_husum_2x3_5rh
-  data_files:
-  - split: train
-    path: dataset_is_husum_2x3_5rh/train-*
-  - split: test
-    path: dataset_is_husum_2x3_5rh/test-*
-- config_name: dataset_is_husum_4x5_5rh
-  data_files:
-  - split: train
-    path: dataset_is_husum_4x5_5rh/train-*
-  - split: test
-    path: dataset_is_husum_4x5_5rh/test-*
-- config_name: dataset_nb_hus_2x3_5rh
-  data_files:
-  - split: train
-    path: dataset_nb_hus_2x3_5rh/train-*
-  - split: test
-    path: dataset_nb_hus_2x3_5rh/test-*
-- config_name: dataset_nb_hus_4x5_5rh
-  data_files:
-  - split: train
-    path: dataset_nb_hus_4x5_5rh/train-*
-  - split: test
-    path: dataset_nb_hus_4x5_5rh/test-*
-- config_name: dataset_nn_hus_2x3_5rh
-  data_files:
-  - split: train
-    path: dataset_nn_hus_2x3_5rh/train-*
-  - split: test
-    path: dataset_nn_hus_2x3_5rh/test-*
-- config_name: dataset_nn_hus_4x5_5rh
-  data_files:
-  - split: train
-    path: dataset_nn_hus_4x5_5rh/train-*
-  - split: test
-    path: dataset_nn_hus_4x5_5rh/test-*
-- config_name: dataset_sv_hus_2x3_5rh
-  data_files:
-  - split: train
-    path: dataset_sv_hus_2x3_5rh/train-*
-  - split: test
-    path: dataset_sv_hus_2x3_5rh/test-*
-- config_name: dataset_sv_hus_4x5_5rh
-  data_files:
-  - split: train
-    path: dataset_sv_hus_4x5_5rh/train-*
-  - split: test
-    path: dataset_sv_hus_4x5_5rh/test-*
-dataset_info:
-- config_name: dataset_da_huse_2x3_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 186251
-    num_examples: 128
-  - name: test
-    num_bytes: 1486529
-    num_examples: 1024
-  download_size: 203726
-  dataset_size: 1672780
-- config_name: dataset_da_huse_4x5_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-    - name: object_3
-      sequence: string
-    - name: object_4
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 386741
-    num_examples: 128
-  - name: test
-    num_bytes: 3057562
-    num_examples: 1024
-  download_size: 512397
-  dataset_size: 3444303
-- config_name: dataset_da_smoerrebroed_2x3_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 226795
-    num_examples: 128
-  - name: test
-    num_bytes: 1806513
-    num_examples: 1024
-  download_size: 219013
-  dataset_size: 2033308
-- config_name: dataset_da_smoerrebroed_4x5_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-    - name: object_3
-      sequence: string
-    - name: object_4
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 445587
-    num_examples: 128
-  - name: test
-    num_bytes: 3571817
-    num_examples: 1024
-  download_size: 547859
-  dataset_size: 4017404
-- config_name: dataset_de_hauser_2x3_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 210461
-    num_examples: 128
-  - name: test
-    num_bytes: 1681221
-    num_examples: 1024
-  download_size: 212285
-  dataset_size: 1891682
-- config_name: dataset_de_hauser_4x5_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-    - name: object_3
-      sequence: string
-    - name: object_4
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 414711
-    num_examples: 128
-  - name: test
-    num_bytes: 3306651
-    num_examples: 1024
-  download_size: 525426
-  dataset_size: 3721362
-- config_name: dataset_en_houses_2x3_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 187565
-    num_examples: 128
-  - name: test
-    num_bytes: 1498622
-    num_examples: 1024
-  download_size: 200675
-  dataset_size: 1686187
-- config_name: dataset_en_houses_4x5_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-    - name: object_3
-      sequence: string
-    - name: object_4
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 390474
-    num_examples: 128
-  - name: test
-    num_bytes: 3130712
-    num_examples: 1024
-  download_size: 513798
-  dataset_size: 3521186
-- config_name: dataset_fo_hus_2x3_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 206735
-    num_examples: 128
-  - name: test
-    num_bytes: 1647768
-    num_examples: 1024
-  download_size: 216372
-  dataset_size: 1854503
-- config_name: dataset_fo_hus_4x5_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-    - name: object_3
-      sequence: string
-    - name: object_4
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 419235
-    num_examples: 128
-  - name: test
-    num_bytes: 3352975
-    num_examples: 1024
-  download_size: 540386
-  dataset_size: 3772210
-- config_name: dataset_is_husum_2x3_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 196218
-    num_examples: 128
-  - name: test
-    num_bytes: 1579934
-    num_examples: 1024
-  download_size: 204625
-  dataset_size: 1776152
-- config_name: dataset_is_husum_4x5_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-    - name: object_3
-      sequence: string
-    - name: object_4
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 416366
-    num_examples: 128
-  - name: test
-    num_bytes: 3329711
-    num_examples: 1024
-  download_size: 532681
-  dataset_size: 3746077
-- config_name: dataset_nb_hus_2x3_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 183889
-    num_examples: 128
-  - name: test
-    num_bytes: 1464132
-    num_examples: 1024
-  download_size: 200028
-  dataset_size: 1648021
-- config_name: dataset_nb_hus_4x5_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-    - name: object_3
-      sequence: string
-    - name: object_4
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 376601
-    num_examples: 128
-  - name: test
-    num_bytes: 3022073
-    num_examples: 1024
-  download_size: 506897
-  dataset_size: 3398674
-- config_name: dataset_nn_hus_2x3_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 183493
-    num_examples: 128
-  - name: test
-    num_bytes: 1478353
-    num_examples: 1024
-  download_size: 200746
-  dataset_size: 1661846
-- config_name: dataset_nn_hus_4x5_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-    - name: object_3
-      sequence: string
-    - name: object_4
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 379289
-    num_examples: 128
-  - name: test
-    num_bytes: 3036246
-    num_examples: 1024
-  download_size: 510417
-  dataset_size: 3415535
-- config_name: dataset_sv_hus_2x3_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 186037
-    num_examples: 128
-  - name: test
-    num_bytes: 1477385
-    num_examples: 1024
-  download_size: 203972
-  dataset_size: 1663422
-- config_name: dataset_sv_hus_4x5_5rh
-  features:
-  - name: introduction
-    dtype: string
-  - name: clues
-    sequence: string
-  - name: question
-    dtype: string
-  - name: format_instructions
-    dtype: string
-  - name: format_example
-    dtype: string
-  - name: solution
-    struct:
-    - name: object_1
-      sequence: string
-    - name: object_2
-      sequence: string
-    - name: object_3
-      sequence: string
-    - name: object_4
-      sequence: string
-  - name: clue_types
-    sequence: string
-  - name: red_herrings
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 386173
-    num_examples: 128
-  - name: test
-    num_bytes: 3078935
-    num_examples: 1024
-  download_size: 519763
-  dataset_size: 3465108
----
+---
+license: apache-2.0
+configs:
+- config_name: dataset_da_huse_2x3_5rh
+  data_files:
+  - split: train
+    path: dataset_da_huse_2x3_5rh/train-*
+  - split: test
+    path: dataset_da_huse_2x3_5rh/test-*
+- config_name: dataset_da_huse_4x5_5rh
+  data_files:
+  - split: train
+    path: dataset_da_huse_4x5_5rh/train-*
+  - split: test
+    path: dataset_da_huse_4x5_5rh/test-*
+- config_name: dataset_da_smoerrebroed_2x3_5rh
+  data_files:
+  - split: train
+    path: dataset_da_smoerrebroed_2x3_5rh/train-*
+  - split: test
+    path: dataset_da_smoerrebroed_2x3_5rh/test-*
+- config_name: dataset_da_smoerrebroed_4x5_5rh
+  data_files:
+  - split: train
+    path: dataset_da_smoerrebroed_4x5_5rh/train-*
+  - split: test
+    path: dataset_da_smoerrebroed_4x5_5rh/test-*
+- config_name: dataset_de_hauser_2x3_5rh
+  data_files:
+  - split: train
+    path: dataset_de_hauser_2x3_5rh/train-*
+  - split: test
+    path: dataset_de_hauser_2x3_5rh/test-*
+- config_name: dataset_de_hauser_4x5_5rh
+  data_files:
+  - split: train
+    path: dataset_de_hauser_4x5_5rh/train-*
+  - split: test
+    path: dataset_de_hauser_4x5_5rh/test-*
+- config_name: dataset_en_houses_2x3_5rh
+  data_files:
+  - split: train
+    path: dataset_en_houses_2x3_5rh/train-*
+  - split: test
+    path: dataset_en_houses_2x3_5rh/test-*
+- config_name: dataset_en_houses_4x5_5rh
+  data_files:
+  - split: train
+    path: dataset_en_houses_4x5_5rh/train-*
+  - split: test
+    path: dataset_en_houses_4x5_5rh/test-*
+- config_name: dataset_fo_hus_2x3_5rh
+  data_files:
+  - split: train
+    path: dataset_fo_hus_2x3_5rh/train-*
+  - split: test
+    path: dataset_fo_hus_2x3_5rh/test-*
+- config_name: dataset_fo_hus_4x5_5rh
+  data_files:
+  - split: train
+    path: dataset_fo_hus_4x5_5rh/train-*
+  - split: test
+    path: dataset_fo_hus_4x5_5rh/test-*
+- config_name: dataset_is_husum_2x3_5rh
+  data_files:
+  - split: train
+    path: dataset_is_husum_2x3_5rh/train-*
+  - split: test
+    path: dataset_is_husum_2x3_5rh/test-*
+- config_name: dataset_is_husum_4x5_5rh
+  data_files:
+  - split: train
+    path: dataset_is_husum_4x5_5rh/train-*
+  - split: test
+    path: dataset_is_husum_4x5_5rh/test-*
+- config_name: dataset_nb_hus_2x3_5rh
+  data_files:
+  - split: train
+    path: dataset_nb_hus_2x3_5rh/train-*
+  - split: test
+    path: dataset_nb_hus_2x3_5rh/test-*
+- config_name: dataset_nb_hus_4x5_5rh
+  data_files:
+  - split: train
+    path: dataset_nb_hus_4x5_5rh/train-*
+  - split: test
+    path: dataset_nb_hus_4x5_5rh/test-*
+- config_name: dataset_nn_hus_2x3_5rh
+  data_files:
+  - split: train
+    path: dataset_nn_hus_2x3_5rh/train-*
+  - split: test
+    path: dataset_nn_hus_2x3_5rh/test-*
+- config_name: dataset_nn_hus_4x5_5rh
+  data_files:
+  - split: train
+    path: dataset_nn_hus_4x5_5rh/train-*
+  - split: test
+    path: dataset_nn_hus_4x5_5rh/test-*
+- config_name: dataset_sv_hus_2x3_5rh
+  data_files:
+  - split: train
+    path: dataset_sv_hus_2x3_5rh/train-*
+  - split: test
+    path: dataset_sv_hus_2x3_5rh/test-*
+- config_name: dataset_sv_hus_4x5_5rh
+  data_files:
+  - split: train
+    path: dataset_sv_hus_4x5_5rh/train-*
+  - split: test
+    path: dataset_sv_hus_4x5_5rh/test-*
+dataset_info:
+- config_name: dataset_da_huse_2x3_5rh
+  features:
+  - name: introduction
+    dtype: string
+  - name: clues
+    sequence: string
+  - name: question
+    dtype: string
+  - name: format_instructions
+    dtype: string
+  - name: format_example
+    dtype: string
+  - name: solution
+    struct:
+    - name: object_1
+      sequence: string
+    - name: object_2
+      sequence: string
+  - name: clue_types
+    sequence: string
+  - name: red_herrings
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+    num_examples: 128
+  - name: test
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+    num_examples: 1024
+  download_size: 203726
+  dataset_size: 1672780
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+  features:
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+  - name: clues
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+  - name: clues
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+  - name: clues
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+  features:
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+    dtype: string
+  - name: clues
+    sequence: string
+  - name: question
+    dtype: string
+  - name: format_instructions
+    dtype: string
+  - name: format_example
+    dtype: string
+  - name: solution
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+    - name: object_2
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+  features:
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+  - name: clues
+    sequence: string
+  - name: question
+    dtype: string
+  - name: format_instructions
+    dtype: string
+  - name: format_example
+    dtype: string
+  - name: solution
+    struct:
+    - name: object_1
+      sequence: string
+    - name: object_2
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+    - name: object_3
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+    - name: object_4
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+  - name: red_herrings
+    sequence: int64
+  splits:
+  - name: train
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+    num_examples: 128
+  - name: test
+    num_bytes: 3078935
+    num_examples: 1024
+  download_size: 519763
+  dataset_size: 3465108
+---
+
+# Dataset Card for Dataset Name
+
+This dataset includes zebra puzzles in multiple European languages and in two sizes: 2x3 and 4x5. It can be used for evaluating logical reasoning ability. 
+
+The data has been generated using the code in [this repo](https://github.com/alexandrainst/zebra_puzzles).
+
+## Dataset Details
+
+### Dataset Description
+
+Zebra puzzles are a type of constraint satisfaction problem. They describe a number of objects, N_objects, that each have attributes, N_attributes. 
+The goal is to couple the objects with the correct attributes, given some clues. Each solution can be described as a N_objects x N_attributes matrix.
+
+To increase difficulty, we include "red herrings" which follow the same structure as true clues, but contain no relevant information. We use 5 red herrings per puzzle.
+
+Most dataset folders contain puzzles with the "houses" theme, where the objects are houses and each attribute describes an inhabitant. 
+Attributes are randomly selected categories such as nationalities and jobs.
+This is included in Danish, English, Faroese, German, Icelandic, Norwegian Bokmål, Norwegian Nynorsk and Swedish. A Dutch version is in progress.
+
+We are currently testing changes to template phrasing in the Danish version, so these may differ slightly from the rest.
+
+We also include data with the "smøerrebrød" theme, where the objects are smørrebrød (open sandwiches) and each attribute is an ingredient. 
+Categories are ingredient types such as bread or garnish.
+This theme is only included in Danish.
+
+The dataset includes puzzles, solutions, lists of included clue types and indices of red herring clues.
+
+The training sets contain 128 puzzles each which are meant as examples for practise. The test sets contain 1024 puzzles each.
+
+
+- **Curated by:** Sofie Helene Bruun (sofie.bruun@alexandra.dk) from the Alexandra Institute.
+- **Funded by [optional]:** [More Information Needed]
+- **Language(s) (NLP):** Danish (da), English (en), Faroese (fo), German (de), Icelandic (is), Norwegian Bokmål (nb), Norwegian Nynorsk (nn) and Swedish (sv).
+- **License:** apache-2.0
+
+### Dataset Sources
+
+- **Repository:** https://github.com/alexandrainst/zebra_puzzles
+- **Paper:** In progress.
+
+## Uses
+
+<!-- Address questions around how the dataset is intended to be used. -->
+
+Logical reasoning ability can be evaluated by comparing reponses to puzzles to the true solutions. For examples of how this can be done, see the associated repository.
+
+The dataset contains examples of the suggested JSON format of reponses for evaluation of LLM's.
+
+Part of the dataset is intended for use in [EuroEval](https://github.com/EuroEval/EuroEval).
+
+### Direct Use
+
+<!-- This section describes suitable use cases for the dataset. -->
+
+Each puzzle can be combined from the columns: introduction, clues and question.
+
+Evaluation can be performed by comparing a response to the solution column.
+
+When evaluating LLM's, consider including the format_instructions and format_example columns in each puzzle, so it is clear how the intended response should be formatted.
+
+To create puzzles without red herrings, remove the clues with indices defined in the red_herrings column.
+
+To analyse the effect of different clue types and red herrings, the clue_types and red_herrings columns can be compared to model performance.
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
+
+The clue_types and red_herrings columns should not be included during the solving process, as they will reduce the need for understanding the natural language prompt.
+Of course, the solution column should also not be included.
+
+## Dataset Structure
+
+<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
+
+Each puzzle is generated randomly and independently of other puzzles.
+
+The columns are:
+
+- *introduction* (str): Defines the overall rules and introduces the attributes.
+- *clues* (list[str]): Clues relating the attributes and objects. 5 red herrings are included per puzzle.
+- *question* (str): The question to answer by a solution.
+- *format_instructions* (str): Instructions on how to respond in JSON format. This is relevant for LLM's.
+- *format_example* (str). An example of the reponse format with the included attribute categories from the puzzle (but not the exact attributes).
+- *solution*. The solution matrix in JSON format.
+- *clue_types*. The list of clue types matching the clues column. 
+- *red_herrings*. A list of indices to the red herring clues.
+
+## Dataset Creation
+
+### Curation Rationale
+
+<!-- Motivation for the creation of this dataset. -->
+
+The motivation is creating a multilingual benchmark for logical reasoning. The data allows us to compare logical reasoning ability of LLM's and compare scores across languages.
+
+Most of the dataset follows the traditional house theme, which is easy to translate. 
+The smørrebrød theme is included to make it possible to compare the house theme to puzzles matching a European culture tied to a specific language.
+
+
+### Source Data
+
+<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
+
+The data is created from words and phrases defined in the zebra puzzle repository.
+
+#### Data Collection and Processing
+
+<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
+
+The included words and phrases have been drafted by the author with the help of Google Translate, GPT-4.1 in Github Copilot, dictionaries and Wikipedia. 
+Relevant code and a few puzzles have been evaluated by native/fluent speakers of each included language. 
+More details are included in the paper in progress.
+
+#### Who are the source data producers?
+
+<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
+
+Sofie Helene Bruun from the Alexandra Institute with help from other people involved in LLM evaluation across Europe.
+
+### Annotations [optional]
+
+<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
+
+#### Annotation process
+
+<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
+
+The puzzles and solutions are automatically generated to match.
+
+#### Who are the annotators?
+
+<!-- This section describes the people or systems who created the annotations. -->
+
+None.
+
+#### Personal and Sensitive Information
+
+<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
+
+No personal or sensitive information is included.
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+Not every combination of words in the dataset has been read by a native speaker of each language, so there is a risk that an included combination sounds unnatural or creates an unintended meaning.
+
+Attributes are combined randomly and might accidentally match stereotypes or traits of real people.
+
+The randomly generated smørrebrød are typically not representative of traditional Danish cuisine, although many of the ingredients are.
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+
+If you use this dataset in your research, please cite our paper:
+
+**BibTeX:**
+
+[Paper in progress]
+
+**APA:**
+
+[Paper in progress]
+
+
+## Dataset Card Contact
+
+sofie.bruun@alexandra.dk