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README.md

@@ -11,9 +11,9 @@ tags:
 
 Dataset contains articles from Wikipedia Bahasa Indonesia which fulfill these conditions:
 - The pages contain many noun phrases, which the authors subjectively pick: (i) fictional plots, e.g., subtitles for films,
-  TV show episodes, and novel stories; (ii) biographies (incl. fictional characters); and (iii) historical events or important events.
+TV show episodes, and novel stories; (ii) biographies (incl. fictional characters); and (iii) historical events or important events.
 - The pages contain significant variation of pronoun and named-entity. We count the number of first, second, third person pronouns,
-  and clitic pronouns in the document by applying string matching.We examine the number
+and clitic pronouns in the document by applying string matching.We examine the number
 of named-entity using the Stanford CoreNLP
 NER Tagger (Manning et al., 2014) with a
 model trained from the Indonesian corpus
@@ -36,25 +36,25 @@ ind
 ## Supported Tasks
 
 Coreference Resolution
-    
+
 ## Dataset Usage
 ### Using `datasets` library
 ```
-    from datasets import load_dataset
-    dset = datasets.load_dataset("SEACrowd/indocoref", trust_remote_code=True)
+from datasets import load_dataset
+dset = datasets.load_dataset("SEACrowd/indocoref", trust_remote_code=True)
 ```
 ### Using `seacrowd` library
 ```import seacrowd as sc
 # Load the dataset using the default config
-    dset = sc.load_dataset("indocoref", schema="seacrowd")
+dset = sc.load_dataset("indocoref", schema="seacrowd")
 # Check all available subsets (config names) of the dataset
-    print(sc.available_config_names("indocoref"))
+print(sc.available_config_names("indocoref"))
 # 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