Update README.md

README.md

@@ -128,6 +128,21 @@ This dataset contains the [Quora](https://huggingface.co/datasets/quora) Questio
 * Collection strategy: Filtering away the "different" options from the `pair-class` subset, removing the label column, and renaming the columns.
 * Deduplified: No
 
+### `triplet-all` subset
+
+* Columns: "anchor", "positive", "negative"
+* Column types: `str`, `str`, `str`
+* Examples:
+    ```python
+    {
+      'anchor': 'Why in India do we not have one on one political debate as in USA?",
+      'positive': 'Why cant we have a public debate between politicians in India like the one in US?',
+      'negative': 'Can people on Quora stop India Pakistan debate? We are sick and tired seeing this everyday in bulk?',
+    }
+    ```
+* Collection strategy: Taken from [embedding-training-data](https://huggingface.co/datasets/sentence-transformers/embedding-training-data), which states: "Duplicate question pairs from Quora with additional hard negatives (mined & denoised by cross-encoder)". Then, take all possible triplet pairs.
+* Deduplified: No
+
 ### `triplet` subset
 
 * Columns: "anchor", "positive", "negative"
@@ -140,5 +155,5 @@ This dataset contains the [Quora](https://huggingface.co/datasets/quora) Questio
       'negative': 'Can people on Quora stop India Pakistan debate? We are sick and tired seeing this everyday in bulk?',
     }
     ```
-* Collection strategy: Taken from [embedding-training-data](https://huggingface.co/datasets/sentence-transformers/embedding-training-data), which states: "Duplicate question pairs from Quora with additional hard negatives (mined & denoised by cross-encoder)".
+* Collection strategy: Taken from [embedding-training-data](https://huggingface.co/datasets/sentence-transformers/embedding-training-data), which states: "Duplicate question pairs from Quora with additional hard negatives (mined & denoised by cross-encoder)". Then, take the anchor, positive and the first negative of each sample.
 * Deduplified: No