Add wh_questions_subject_gap_long_distance data files

README.md

@@ -1780,10 +1780,10 @@ dataset_info:
     dtype: int32
   splits:
   - name: train
-    num_bytes: 269665
+    num_bytes: 268270
     num_examples: 1000
-  download_size: 462660
-  dataset_size: 269665
+  download_size: 98913
+  dataset_size: 268270
 - config_name: wh_vs_that_no_gap
   features:
   - name: sentence_good
@@ -2145,6 +2145,10 @@ configs:
   data_files:
   - split: train
     path: wh_questions_subject_gap/train-*
+- config_name: wh_questions_subject_gap_long_distance
+  data_files:
+  - split: train
+    path: wh_questions_subject_gap_long_distance/train-*
 ---
 
 # Dataset Card for "blimp"

dataset_infos.json

@@ -4223,62 +4223,50 @@
         "features": {
             "sentence_good": {
                 "dtype": "string",
-                "id": null,
                 "_type": "Value"
             },
             "sentence_bad": {
                 "dtype": "string",
-                "id": null,
                 "_type": "Value"
             },
             "field": {
                 "dtype": "string",
-                "id": null,
                 "_type": "Value"
             },
             "linguistics_term": {
                 "dtype": "string",
-                "id": null,
                 "_type": "Value"
             },
             "UID": {
                 "dtype": "string",
-                "id": null,
                 "_type": "Value"
             },
             "simple_LM_method": {
                 "dtype": "bool",
-                "id": null,
                 "_type": "Value"
             },
             "one_prefix_method": {
                 "dtype": "bool",
-                "id": null,
                 "_type": "Value"
             },
             "two_prefix_method": {
                 "dtype": "bool",
-                "id": null,
                 "_type": "Value"
             },
             "lexically_identical": {
                 "dtype": "bool",
-                "id": null,
                 "_type": "Value"
             },
             "pair_id": {
                 "dtype": "int32",
-                "id": null,
                 "_type": "Value"
             }
         },
-        "supervised_keys": null,
         "builder_name": "blimp",
+        "dataset_name": "blimp",
         "config_name": "wh_questions_subject_gap_long_distance",
         "version": {
             "version_str": "0.1.0",
-            "description": null,
-            "datasets_version_to_prepare": null,
             "major": 0,
             "minor": 1,
             "patch": 0
@@ -4286,20 +4274,14 @@
         "splits": {
             "train": {
                 "name": "train",
-                "num_bytes": 269665,
+                "num_bytes": 268270,
                 "num_examples": 1000,
-                "dataset_name": "blimp"
-            }
-        },
-        "download_checksums": {
-            "https://raw.githubusercontent.com/alexwarstadt/blimp/master/data/wh_questions_subject_gap_long_distance.jsonl": {
-                "num_bytes": 462660,
-                "checksum": "985bae202dbc5566b9b5c51bd77dd9d1dbcd87e0f38e008c34a11d7aa07db788"
+                "dataset_name": null
             }
         },
-        "download_size": 462660,
-        "dataset_size": 269665,
-        "size_in_bytes": 732325
+        "download_size": 98913,
+        "dataset_size": 268270,
+        "size_in_bytes": 367183
     },
     "wh_vs_that_no_gap": {
         "description": "\nBLiMP is a challenge set for evaluating what language models (LMs) know about\nmajor grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each\ncontaining 1000 minimal pairs isolating specific contrasts in syntax,\nmorphology, or semantics. The data is automatically generated according to\nexpert-crafted grammars.\n",

wh_questions_subject_gap_long_distance/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ca30473b9569b256cc7707d02668db436d097c810466c8cb60b1b7315ddb10e9
+size 98913