:sparkles: fix columns name

README.md

@@ -37,10 +37,10 @@ task_ids:
   - [Dataset Structure](#dataset-structure)
     - [Data Instances](#data-instances)
       - [base](#base)
-      - [original](#original)
+      - [stress](#stress)
     - [Data Fields](#data-fields)
       - [base](#base-1)
-      - [original](#original-1)
+      - [original](#original)
     - [Data Splits](#data-splits)
     - [Annotations](#annotations)
   - [Additional Information](#additional-information)
@@ -90,16 +90,12 @@ print(dataset)
 #     })
 # })
 
-dataset: ds.DatasetDict = ds.load_dataset("hpprc/jsick", name="original")
+dataset: ds.DatasetDict = ds.load_dataset("hpprc/jsick", name="stress")
 print(dataset)
 # DatasetDict({
-#     train: Dataset({
-#         features: ['id', 'premise', 'hypothesis', 'label', 'score', 'sentence_A_En', 'sentence_B_En', 'entailment_label_En', 'relatedness_score_En', 'corr_entailment_labelAB_En', 'corr_entailment_labelBA_En', 'image_ID', 'original_caption', 'semtag_short', 'semtag_long'],
-#         num_rows: 4500
-#     })
 #     test: Dataset({
-#         features: ['id', 'premise', 'hypothesis', 'label', 'score', 'sentence_A_En', 'sentence_B_En', 'entailment_label_En', 'relatedness_score_En', 'corr_entailment_labelAB_En', 'corr_entailment_labelBA_En', 'image_ID', 'original_caption', 'semtag_short', 'semtag_long'],
-#         num_rows: 4927
+#         features: ['id', 'premise', 'hypothesis', 'label', 'score', 'sentence_A_Ja_origin', 'entailment_label_origin', 'relatedness_score_Ja_origin', 'rephrase_type', 'case_particles'],
+#         num_rows: 900
 #     })
 # })
 ```
@@ -110,31 +106,30 @@ print(dataset)
 An example of looks as follows:
 
 ```json
-{
-  'id': 12,
-  'premise': '若者がフットボール選手を見ている',
-  'hypothesis': 'フットボール選手を若者が見ている',
-  'label': 0,
-  'heuristics': 'overlap-full',
-  'number_of_NPs': 2,
-  'semtag': 'scrambling'
+{'id': 1,
+'premise': '子供たちのグループが庭で遊んでいて、後ろの方には年を取った男性が立っている',
+'hypothesis': '庭にいる男の子たちのグループが遊んでいて、男性が後ろの方に立っている',
+'label': 1,
+'score': 3.700000047683716,
+'sentence_A_En': 'A group of kids is playing in a yard and an old man is standing in the background',
+'sentence_B_En': 'A group of boys in a yard is playing and a man is standing in the background',
+'entailment_label_En': 1,
+'relatedness_score_En': 4.5,
+'corr_entailment_labelAB_En': 'nan',
+'corr_entailment_labelBA_En': 'nan',
+'image_ID': '3155657768_b83a7831e5.jpg',
+'original_caption': 'A group of children playing in a yard , a man in the background .',
+'semtag_short': 'nan',
+'semtag_long': 'nan',
 }
 ```
 
-#### original
+#### stress
 
 An example of looks as follows:
 
 ```json
-{
-  'id': 12,
-  'sentence_A_Ja': '若者がフットボール選手を見ている',
-  'sentence_B_Ja': 'フットボール選手を若者が見ている',
-  'entailment_label_Ja': 0,
-  'heuristics': 'overlap-full',
-  'number_of_NPs': 2,
-  'semtag': 'scrambling'
-}
+{'id': '5818_de_d', 'premise': '女性火の近くダンスをしている', 'hypothesis': '火の近くでダンスをしている女性は一人もいない', 'label': 2, 'score': 4.0, 'sentence_A_Ja_origin': '女性が火の近くでダンスをしている', 'entailment_label_origin': 2, 'relatedness_score_Ja_origin': 3.700000047683716, 'rephrase_type': 'd', 'case_particles': 'de'}
 ```
 
 ### Data Fields

jsick.py

@@ -70,10 +70,10 @@ class JSICKDataset(ds.GeneratorBasedBuilder):
                     "hypothesis": ds.Value("string"),
                     "label": labels,
                     "score": ds.Value("float32"),
-                    "sentence_A_En": ds.Value("string"),
-                    "sentence_B_En": ds.Value("string"),
-                    "entailment_label_En": labels,
-                    "relatedness_score_En": ds.Value("float32"),
+                    "premise_en": ds.Value("string"),
+                    "hypothesis_en": ds.Value("string"),
+                    "label_en": labels,
+                    "score_en": ds.Value("float32"),
                     "corr_entailment_labelAB_En": ds.Value("string"),
                     "corr_entailment_labelBA_En": ds.Value("string"),
                     "image_ID": ds.Value("string"),
@@ -176,6 +176,10 @@ class JSICKDataset(ds.GeneratorBasedBuilder):
                     "sentence_B_Ja": "hypothesis",
                     "entailment_label_Ja": "label",
                     "relatedness_score_Ja": "score",
+                    "sentence_A_En": "premise_en",
+                    "sentence_B_En": "hypothesis_en",
+                    "entailment_label_En": "label_en",
+                    "relatedness_score_En": "score_en",
                 }
             )