Update README.md

README.md

@@ -115,7 +115,7 @@ This dataset is a collection of **Multi-hop Inference** and **Mixed-hop Predicti
 - **Multi-hop Inference**: This task aims to evaluate the model’s ability in deducing indirect, multi-hop subsumptions from direct, one-hop subsumptions, so as to simulate transitive inference.
 - **Mixed-hop Prediction**: This task aims to evaluate the model’s capability in determining the existence of subsumption relationships between arbitrary entity pairs, where the entities are not necessarily seen during training. The transfer setting of this task involves training models on asserted training edges of one hierarchy testing on arbitrary entity pairs of another.
 
-See our published paper (link below) for more detail.
+See our published [paper](https://arxiv.org/abs/2401.11374) for more detail.
 
 
 ## Links
@@ -123,7 +123,7 @@ See our published paper (link below) for more detail.
 - **GitHub Repository:** https://github.com/KRR-Oxford/HierarchyTransformers
 - **Huggingface Page**: https://huggingface.co/Hierarchy-Transformers
 - **Zenodo Release**: https://doi.org/10.5281/zenodo.10511042 
-- **Paper:** [Language Models as Hierarchy Encoders]((https://arxiv.org/abs/2401.11374)) (NeurIPS 2024).
+- **Paper:** [Language Models as Hierarchy Encoders](https://arxiv.org/abs/2401.11374) (NeurIPS 2024).
 
 The information of original entity IDs is not available in the Huggingface release; To map entities back to their original hierarchies, refer to this [Zenodo release](https://doi.org/10.5281/zenodo.10511042).
 
@@ -137,9 +137,15 @@ Each subset in this dataset follows the naming convention `TaskType-NegativeType
 - `NegativeType`: Either `RandomNegatives` or `HardNegatives`, specifying the strategy used for negative sampling.
 
 - `SampleStructure`: Either `Triplets` or `Pairs`, indicating the format of the samples.
-  - In `Triplets`, each sample is structured as `(child, parent, negative)`.
+  - In `Triplets`, each sample is structured as `(child, parent, negative)`. 
   - In `Pairs`, each sample is a labelled pair `(child, parent, label)`, where `label=1` denotes a positive subsumption and `label=0` denotes a negative subsumption.
 
+For example, to load a subset for the **Mixed-hop Prediction** task with **random negatives** and samples presented as **triplets**, we can use the following command:
+
+```python
+from datasets import load_dataset
+dataset = load_dataset("Hierarchy-Transformers/WordNetNoun", "MixedHop-RandomNegatives-Triplets")
+```
 
 ## Citation