Update README.md

README.md

@@ -110,29 +110,29 @@ language:
 
 
 
-# GRADIEND Race Data
+# GRADIEND Religion Data
 
 <!-- Provide a quick summary of the dataset. -->
 
-This dataset consists of templated sentences with the masked word being sensitive to race, e.g., *African*. 
+This dataset consists of templated sentences with the masked word being sensitive to religion, e.g., *Jewish*. 
 ```
 
 ```
 
-See [GENTER](https://huggingface.co/datasets/aieng-lab/genter) and [GRADIEND Religion Data](https://huggingface.co/datasets/aieng-lab/gradiend_religion_data) for similar datasets.
+See [GENTER](https://huggingface.co/datasets/aieng-lab/genter) and [GRADIEND Race Data](https://huggingface.co/datasets/aieng-lab/gradiend_race_data) for similar datasets.
 
 ## Usage
 
-The dataset uses **one subset per class**. Subset names are class identifiers: `white`, `black`, `asian`. Each subset has columns `masked`, `split`, and one column per class (e.g. `white`, `black`, `asian`) giving the token for that class in that row.
+The dataset uses **one subset per class**. Subset names are class identifiers: `jewish`, `christian`, `muslim`. Each subset has columns `masked`, `split`, and one column per class (e.g. `christian`, `jewish`, `muslim`) giving the token for that class in that row.
 
 ```python
 from datasets import load_dataset
 
-# Load one subset (one class view), e.g. "white"
-ds = load_dataset("aieng-lab/gradiend_race_data", "white", split="train")
-# ds has columns: masked, split, white, black, asian
-label = ds['white']
-alternative_target = ds['black'] # or 'asian'
+# Load one subset (one class view), e.g. "christian"
+ds = load_dataset("aieng-lab/gradiend_religion_data", "christian", split="train")
+# ds has columns: masked, split, christian, jewish, muslim
+label = ds['christian']
+alternative_target = ds['jewish'] # or 'muslim'
 ```
 `split` can be either `train`, `val`, `test`, or `all`.
 
@@ -142,9 +142,9 @@ alternative_target = ds['black'] # or 'asian'
 ### Dataset Description
 
 <!-- Provide a longer summary of what this dataset is. -->
-This dataset is a filtered version of [Wikipedia-10](https://drive.google.com/file/d/1boQTn44RnHdxWeUKQAlRgQ7xrlQ_Glwo/view?usp=sharing) containing only sentences that contain a race bias sensitive word of the `source_id` race. We used the same bias sensitive words as defined by [Maede et al. (2021)](https://arxiv.org/abs/2110.08527) ([bias attribute words](https://github.com/McGill-NLP/bias-bench/blob/main/data/bias_attribute_words.json)).
+This dataset is a filtered version of [Wikipedia-10](https://drive.google.com/file/d/1boQTn44RnHdxWeUKQAlRgQ7xrlQ_Glwo/view?usp=sharing) containing only sentences that contain a religion bias sensitive word of the `source_id` religion. We used the same bias sensitive words as defined by [Maede et al. (2021)](https://arxiv.org/abs/2110.08527) ([bias attribute words](https://github.com/McGill-NLP/bias-bench/blob/main/data/bias_attribute_words.json)).
 
-It is stored in per-class form: each subset (e.g. `white`) corresponds to one source class. Rows are identified by (masked, split). For each other class, the corresponding column holds the target token when that class is the counterfactual target (e.g. column `black` in subset `white` is the token used when the target class is `black`).
+It is stored in per-class form: each subset (e.g. `christian`) corresponds to one source class. Rows are identified by (masked, split). For each other class, the corresponding column holds the target token when that class is the counterfactual target (e.g. column `jewish` in subset `christian` is the token used when the target class is `jewish`).
 
 ### Dataset Sources
 
@@ -161,7 +161,7 @@ It is stored in per-class form: each subset (e.g. `white`) corresponds to one so
 
 - `text`: the original entry of Wikipedia-10
 - `masked`: the masked version of `text` (i.e., contains a `[MASK]` at every occurrence of the subset column)
-- `white`/`asian`/`black`: The mask target words for white/asian/black races. Note that the column equal to the subset id is the original value of the `[MASK]` token. 
+- `christian`/`jewish`/`muslim`: The mask target words for christian/jewish/muslim religions. Note that the column equal to the subset id is the original value of the `[MASK]` token. 
 
 
 ## Dataset Creation
@@ -170,7 +170,7 @@ It is stored in per-class form: each subset (e.g. `white`) corresponds to one so
 
 <!-- Motivation for the creation of this dataset. -->
 
-For the training of a race bias [GRADIEND models](https://github.com/aieng-lab/gradiend), a diverse dataset is required to asses model gradients relevant to bias-sensitive information.
+For the training of a religion bias [GRADIEND models](https://github.com/aieng-lab/gradiend), a diverse dataset is required to asses model gradients relevant to bias-sensitive information.
 
 ### Source Data
 
@@ -181,7 +181,7 @@ The dataset is derived from [Wikipedia-10](https://drive.google.com/file/d/1boQT
 
 ### Limitations
 
-Note that the splitting is performed entirely random. Thus, the same masked text might occur in other splits (in combination with other target words). The same limitation holds across different races.
+Note that the splitting is performed entirely random. Thus, the same masked text might occur in other splits (in combination with other target words). The same limitation holds across different religions.
 
 
 ## Citation