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README.md

@@ -12,25 +12,25 @@ tags:
 Nergrit Corpus is a dataset collection of Indonesian Named Entity Recognition (NER), Statement Extraction,
 and Sentiment Analysis developed by PT Gria Inovasi Teknologi (GRIT).
 The Named Entity Recognition contains 18 entities as follow:
-    'CRD': Cardinal
-    'DAT': Date
-    'EVT': Event
-    'FAC': Facility
-    'GPE': Geopolitical Entity
-    'LAW': Law Entity (such as Undang-Undang)
-    'LOC': Location
-    'MON': Money
-    'NOR': Political Organization
-    'ORD': Ordinal
-    'ORG': Organization
-    'PER': Person
-    'PRC': Percent
-    'PRD': Product
-    'QTY': Quantity
-    'REG': Religion
-    'TIM': Time
-    'WOA': Work of Art
-    'LAN': Language
+'CRD': Cardinal
+'DAT': Date
+'EVT': Event
+'FAC': Facility
+'GPE': Geopolitical Entity
+'LAW': Law Entity (such as Undang-Undang)
+'LOC': Location
+'MON': Money
+'NOR': Political Organization
+'ORD': Ordinal
+'ORG': Organization
+'PER': Person
+'PRC': Percent
+'PRD': Product
+'QTY': Quantity
+'REG': Religion
+'TIM': Time
+'WOA': Work of Art
+'LAN': Language
 
 
 ## Languages
@@ -40,25 +40,25 @@ ind
 ## Supported Tasks
 
 Named Entity Recognition
-    
+
 ## Dataset Usage
 ### Using `datasets` library
 ```
-    from datasets import load_dataset
-    dset = datasets.load_dataset("SEACrowd/nergrit", trust_remote_code=True)
+from datasets import load_dataset
+dset = datasets.load_dataset("SEACrowd/nergrit", trust_remote_code=True)
 ```
 ### Using `seacrowd` library
 ```import seacrowd as sc
 # Load the dataset using the default config
-    dset = sc.load_dataset("nergrit", schema="seacrowd")
+dset = sc.load_dataset("nergrit", schema="seacrowd")
 # Check all available subsets (config names) of the dataset
-    print(sc.available_config_names("nergrit"))
+print(sc.available_config_names("nergrit"))
 # Load the dataset using a specific config
-    dset = sc.load_dataset_by_config_name(config_name="<config_name>")
+dset = sc.load_dataset_by_config_name(config_name="<config_name>")
 ```
-    
-    More details on how to load the `seacrowd` library can be found [here](https://github.com/SEACrowd/seacrowd-datahub?tab=readme-ov-file#how-to-use).
-    
+
+More details on how to load the `seacrowd` library can be found [here](https://github.com/SEACrowd/seacrowd-datahub?tab=readme-ov-file#how-to-use).
+
 
 ## Dataset Homepage