Update README.md

README.md

@@ -1,7 +1,9 @@
 ---
 name: WordNetNoun Subsumption (Hypernym) Hierarchy.
 description: >
-  This dataset is a collection of Multi-hop Inference and Mixed-hop Prediction datasets created from WordNet's subsumption (hypernym) hierarchy of noun entities for training and evaluating hierarchy embedding models.
+  This dataset is a collection of Multi-hop Inference and Mixed-hop Prediction
+  datasets created from WordNet's subsumption (hypernym) hierarchy of noun
+  entities for training and evaluating hierarchy embedding models.
 license: apache-2.0
 language:
 - en
@@ -18,7 +20,8 @@ tags:
 configs:
 - config_name: MultiHop-RandomNegatives-Triplets
   description: >
-    A dataset for Multi-hop Inference with random negatives; samples formatted as triplets.
+    A dataset for Multi-hop Inference with random negatives; samples formatted
+    as triplets.
   data_files:
   - split: train
     path: MultiHop-RandomNegatives-Triplets/train*
@@ -28,7 +31,8 @@ configs:
     path: MultiHop-RandomNegatives-Triplets/test*
 - config_name: MultiHop-HardNegatives-Triplets
   description: >
-    A dataset for Multi-hop Inference with hard negatives; samples formatted as triplets.
+    A dataset for Multi-hop Inference with hard negatives; samples formatted as
+    triplets.
   data_files:
   - split: train
     path: MultiHop-HardNegatives-Triplets/train*
@@ -38,7 +42,8 @@ configs:
     path: MultiHop-HardNegatives-Triplets/test*
 - config_name: MixedHop-RandomNegatives-Triplets
   description: >
-    A dataset for Mixed-hop Prediction with random negatives; samples formatted as triplets.
+    A dataset for Mixed-hop Prediction with random negatives; samples formatted
+    as triplets.
   data_files:
   - split: train
     path: MixedHop-RandomNegatives-Triplets/train*
@@ -48,7 +53,8 @@ configs:
     path: MixedHop-RandomNegatives-Triplets/test*
 - config_name: MixedHop-HardNegatives-Triplets
   description: >
-    A dataset for Mixed-hop Prediction with hard negatives; samples formatted as triplets.
+    A dataset for Mixed-hop Prediction with hard negatives; samples formatted as
+    triplets.
   data_files:
   - split: train
     path: MixedHop-HardNegatives-Triplets/train*
@@ -58,7 +64,8 @@ configs:
     path: MixedHop-HardNegatives-Triplets/test*
 - config_name: MultiHop-RandomNegatives-Pairs
   description: >
-    A dataset for Multi-hop Inference with random negatives; samples formatted as pairs.
+    A dataset for Multi-hop Inference with random negatives; samples formatted
+    as pairs.
   data_files:
   - split: train
     path: MultiHop-RandomNegatives-Pairs/train*
@@ -68,7 +75,8 @@ configs:
     path: MultiHop-RandomNegatives-Pairs/test*
 - config_name: MultiHop-HardNegatives-Pairs
   description: >
-    A dataset for Multi-hop Inference with hard negatives; samples formatted as pairs.
+    A dataset for Multi-hop Inference with hard negatives; samples formatted as
+    pairs.
   data_files:
   - split: train
     path: MultiHop-HardNegatives-Pairs/train*
@@ -78,7 +86,8 @@ configs:
     path: MultiHop-HardNegatives-Pairs/test*
 - config_name: MixedHop-RandomNegatives-Pairs
   description: >
-    A dataset for Mixed-hop Prediction with random negatives; samples formatted as pairs.
+    A dataset for Mixed-hop Prediction with random negatives; samples formatted
+    as pairs.
   data_files:
   - split: train
     path: MixedHop-RandomNegatives-Pairs/train*
@@ -88,7 +97,8 @@ configs:
     path: MixedHop-RandomNegatives-Pairs/test*
 - config_name: MixedHop-HardNegatives-Pairs
   description: >
-    A dataset for Mixed-hop Prediction with hard negatives; samples formatted as pairs.
+    A dataset for Mixed-hop Prediction with hard negatives; samples formatted as
+    pairs.
   data_files:
   - split: train
     path: MixedHop-HardNegatives-Pairs/train*
@@ -100,141 +110,50 @@ configs:
 
 # Dataset Card for WordNetNoun
 
-<!-- Provide a quick summary of the dataset. -->
-
 This dataset is a collection of **Multi-hop Inference** and **Mixed-hop Prediction** datasets created from WordNet's subsumption (hypernym) hierarchy of noun entities for training and evaluating hierarchy embedding models.
 
-- 
-
-
-## Dataset Details
-
-### Dataset Description
-
-<!-- Provide a longer summary of what this dataset is. -->
-
-
-
-- **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-
-### Dataset Sources [optional]
-
-<!-- Provide the basic links for the dataset. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the dataset is intended to be used. -->
+- **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.
 
-### Direct Use
+See our published paper (link below) for more detail.
 
-<!-- This section describes suitable use cases for the dataset. -->
 
-[More Information Needed]
+## Links
 
-### Out-of-Scope Use
+- **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).
 
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
+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).
 
-[More Information Needed]
 
 ## Dataset Structure
 
-<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
-
-[More Information Needed]
-
-## Dataset Creation
-
-### Curation Rationale
-
-<!-- Motivation for the creation of this dataset. -->
-
-[More Information Needed]
-
-### Source Data
-
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
-
-#### Data Collection and Processing
-
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-
-[More Information Needed]
-
-#### Who are the source data producers?
-
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-
-[More Information Needed]
-
-### Annotations [optional]
-
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
-
-#### Annotation process
-
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
-
-[More Information Needed]
-
-#### Who are the annotators?
-
-<!-- This section describes the people or systems who created the annotations. -->
-
-[More Information Needed]
-
-#### Personal and Sensitive Information
-
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
+Each subset in this dataset follows the naming convention `TaskType-NegativeType-SampleStructure`:
 
-## Glossary [optional]
+- `TaskType`: Either `MultiHop` or `MixedHop`, indicating the type of hierarchy evaluation task.
 
-<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
+- `NegativeType`: Either `RandomNegatives` or `HardNegatives`, specifying the strategy used for negative sampling.
 
-[More Information Needed]
+- `SampleStructure`: Either `Triplets` or `Pairs`, indicating the format of the samples.
+  - 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.
 
-## More Information [optional]
 
-[More Information Needed]
+## Citation
 
-## Dataset Card Authors [optional]
+The relevant paper has been accepted at NeurIPS 2024 (to appear).
 
-[More Information Needed]
+```
+@article{he2024language,
+  title={Language models as hierarchy encoders},
+  author={He, Yuan and Yuan, Zhangdie and Chen, Jiaoyan and Horrocks, Ian},
+  journal={arXiv preprint arXiv:2401.11374},
+  year={2024}
+}
+```
 
 ## Dataset Card Contact
 
-[More Information Needed]
+Yuan He (`yuan.he(at)cs.ox.ac.uk`)