Updated a tag to make it more discoverable (#1)

- Updated a tag to make it more discoverable (040db3918b765ef925cdc262b8dffd3bcb0395a8)


Co-authored-by: Nathan Butters <[email protected]>

README.md

@@ -5,7 +5,7 @@ task_categories:
 language:
 - en
 tags:
-- Fairness dataste
+- Fairness dataset
 - sentiment analysis
 - Gender
 size_categories:
@@ -15,9 +15,9 @@ size_categories:
 # Sentiment fairness dataset
 ================================
 
-This dataset is to measure gender fairness in the downstream task of sentiment analysis. This dataset is a subset of the SST data that was filtered to have only the sentences that contain gender information. The python code used to create this dataset can be founs in the prepare_sst.ipyth file. 
+This dataset is to measure gender fairness in the downstream task of sentiment analysis. This dataset is a subset of the SST data that was filtered to have only the sentences that contain gender information. The python code used to create this dataset can be found in the prepare_sst.ipyth file. 
 
-Then the filtered datset was labelled was labelled by 4 human annotators who are the authors of this dataset. The annotations instructions are given below.
+Then the filtered datset was labeled by 4 human annotators who are the authors of this dataset. The annotations instructions are given below.
 ---
 
 # Annotation Instructions
@@ -140,7 +140,7 @@ correct: the number of annotators who gave the majority of labels.
 
 incorrect: the number of annotators who gave the minority labels.
 
-**This dataset is ready to use as the majority of hte human annotators agreed that the sentiment of these sentences is atrgeted at teh gender mentioned in the "gender" column**
+**This dataset is ready to use as the majority of the human annotators agreed that the sentiment of these sentences is targeted at the gender mentioned in the "gender" column**
 
 ---
 # Citation
@@ -148,7 +148,7 @@ incorrect: the number of annotators who gave the minority labels.
 
 @misc{sst-sentiment-fainress-dataset,
   title={A dataset to measure fairness in the sentiment analysis task},
-  author={gero,Katy and Butters,Nathan and Bethke, Anna and Elsafoury, Fatma},
+  author={Gero, Katy and Butters, Nathan and Bethke, Anna and Elsafoury, Fatma},
   howpublished={https://github.com/efatmae/SST_sentiment_fairness_data},
   year={2023}
 }