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README.md

@@ -28,7 +28,7 @@ task_ids:
 paperswithcode_id: korean-multi-label-hate-speech-dataset
 dataset_info:
   features:
-  - name: document
+  - name: text
     dtype: string
   - name: label
     sequence:
@@ -113,8 +113,8 @@ Korean
 The dataset is provided with train/validation/test set in the txt format. Each instance is a news comment with a corresponding one or more hate speech classes (labels: `Politics`, `Origin`, `Physical`, `Age`, `Gender`, `Religion`, `Race`, `Profanity`) or `Not Hate Speech` class. The label numbers matching in both English and Korean is in the data fields section. 
 
 ```python
-{'document':'수꼴틀딱시키들이 다 디져야 나라가 똑바로 될것같다..답이 없는 종자들ㅠ'
- 'label': '2,3,4'
+{'text':'수꼴틀딱시키들이 다 디져야 나라가 똑바로 될것같다..답이 없는 종자들ㅠ'
+ 'label': [2, 3, 4]
 }
 ```
 

dataset_infos.json

@@ -4,12 +4,12 @@
         "homepage": "https://github.com/adlnlp/K-MHaS",
         "license": "cc-by-sa-4.0",
         "features": {
-            "document": {
+            "text": {
                 "dtype": "string",
                 "id": null,
                 "_type": "Value"
             },
-            "labels": {
+            "label": {
                 "feature": {
                     "num_classes": 9,
                     "names": [

kmhas_korean_hate_speech.py

@@ -74,7 +74,7 @@ class Kmhas(datasets.GeneratorBasedBuilder):
     def _info(self):
         features = datasets.Features(
             {
-                "document": datasets.Value("string"),
+                "text": datasets.Value("string"),
                 "label": datasets.Sequence(datasets.ClassLabel(names=_CLASS_NAMES))
             }
         )
@@ -108,7 +108,7 @@ class Kmhas(datasets.GeneratorBasedBuilder):
                 sentence = row[0]
                 label = [int(ind) for ind in row[1].split(",")]
                 yield index, {
-                    "document" : sentence,
+                    "text" : sentence,
                     "label": label,              
                 }