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README.md

@@ -19,7 +19,7 @@ task_categories:
 task_ids:
 - fact-checking-retrieval
 paperswithcode_id: hover
-pretty_name: HoVer
+pretty_name: HoVer (Parquet Format)
 dataset_info:
   features:
   - name: id
@@ -54,13 +54,16 @@ dataset_info:
   - name: test
     num_bytes: 927513
     num_examples: 4000
-  download_size: 12257835
+  download_size: 3428352
   dataset_size: 7758943
 ---
 
-# Dataset Card for HoVer
+# Dataset Card for HoVer (Parquet Format)
+
+> **Note**: This is a scriptless, Parquet-based version of the HoVer dataset for seamless integration with HuggingFace `datasets` library. No `trust_remote_code` required!
 
 ## Table of Contents
+- [Quick Start](#quick-start)
 - [Dataset Description](#dataset-description)
   - [Dataset Summary](#dataset-summary)
   - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
@@ -73,119 +76,146 @@ dataset_info:
   - [Curation Rationale](#curation-rationale)
   - [Source Data](#source-data)
   - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
 - [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
   - [Licensing Information](#licensing-information)
   - [Citation Information](#citation-information)
   - [Contributions](#contributions)
 
+## Quick Start
+
+```python
+from datasets import load_dataset
+
+# Load the dataset (no trust_remote_code needed!)
+dataset = load_dataset("vincentkoc/hover-parquet")
+
+# Access splits
+train = dataset["train"]
+validation = dataset["validation"]
+test = dataset["test"]
+
+# Example usage
+print(train[0])
+# {
+#   'id': 0,
+#   'uid': '330ca632-e83f-4011-b11b-0d0158145036',
+#   'claim': 'Skagen Painter Peder Severin Krøyer favored naturalism...',
+#   'supporting_facts': [{'key': 'Kristian Zahrtmann', 'value': 0}, ...],
+#   'label': 1,  # 0: NOT_SUPPORTED, 1: SUPPORTED
+#   'num_hops': 3,
+#   'hpqa_id': '5ab7a86d5542995dae37e986'
+# }
+```
+
 ## Dataset Description
 
 - **Homepage:** https://hover-nlp.github.io/
 - **Repository:** https://github.com/hover-nlp/hover
 - **Paper:** https://arxiv.org/abs/2011.03088
 - **Leaderboard:** https://hover-nlp.github.io/
-- **Point of Contact:** [More Information Needed]
+- **Original Dataset:** https://huggingface.co/datasets/hover
+- **Parquet Version:** https://huggingface.co/datasets/vincentkoc/hover-parquet
 
 ### Dataset Summary
 
-[More Information Needed]
+HoVer (HOP VERification) is an open-domain, many-hop fact extraction and claim verification dataset built upon the Wikipedia corpus. The dataset contains claims that require reasoning over multiple documents (multi-hop) to verify whether they are supported or not supported by evidence.
+
+The original 2-hop claims are adapted from question-answer pairs from HotpotQA. It was collected by a team of NLP researchers at UNC Chapel Hill and Verisk Analytics.
+
+This version provides the dataset in Parquet format for efficient loading and compatibility with modern data processing pipelines, eliminating the need for custom loading scripts.
 
 ### Supported Tasks and Leaderboards
 
-[More Information Needed]
+- **Fact Verification**: Determine whether a claim is SUPPORTED or NOT_SUPPORTED based on evidence from Wikipedia articles
+- **Multi-hop Reasoning**: Claims require reasoning across multiple documents (indicated by `num_hops` field)
+- **Evidence Retrieval**: Identify relevant supporting facts from source documents
+
+The official leaderboard is available at https://hover-nlp.github.io/
 
 ### Languages
 
-[More Information Needed]
+English (en)
 
 ## Dataset Structure
 
 ### Data Instances
 
-A sample training set is provided below
-
-```
-{'id': 14856, 'uid': 'a0cf45ea-b5cd-4c4e-9ffa-73b39ebd78ce', 'claim': 'The park at which Tivolis Koncertsal is located opened on 15 August 1843.', 'supporting_facts': [{'key': 'Tivolis Koncertsal', 'value': 0}, {'key': 'Tivoli Gardens', 'value': 1}], 'label': 'SUPPORTED', 'num_hops': 2, 'hpqa_id': '5abca1a55542993a06baf937'}
+A sample training set example:
+
+```json
+{
+  "id": 14856,
+  "uid": "a0cf45ea-b5cd-4c4e-9ffa-73b39ebd78ce",
+  "claim": "The park at which Tivolis Koncertsal is located opened on 15 August 1843.",
+  "supporting_facts": [
+    {"key": "Tivolis Koncertsal", "value": 0},
+    {"key": "Tivoli Gardens", "value": 1}
+  ],
+  "label": 1,
+  "num_hops": 2,
+  "hpqa_id": "5abca1a55542993a06baf937"
+}
 ```
 
-Please note that in test set sentence only id, uid and claim are available. Labels are not available in test set and are represented by -1.
-
+**Note**: In the test set, only `id`, `uid`, and `claim` fields contain meaningful data. The `label` is set to `-1`, `num_hops` to `-1`, `hpqa_id` to `"None"`, and `supporting_facts` is an empty list, as these are withheld for evaluation purposes.
 
 ### Data Fields
 
-[More Information Needed]
+- **id** (`int32`): Sequential identifier for the example within its split
+- **uid** (`string`): Unique identifier (UUID) for the claim
+- **claim** (`string`): The claim statement to be verified
+- **supporting_facts** (`list`): List of evidence facts, where each fact contains:
+  - **key** (`string`): Title of the Wikipedia article
+  - **value** (`int32`): Sentence index within that article
+- **label** (`ClassLabel`): Verification label with values:
+  - `0`: NOT_SUPPORTED - The claim is not supported by the evidence
+  - `1`: SUPPORTED - The claim is supported by the evidence
+  - `-1`: Unknown (used in test set)
+- **num_hops** (`int32`): Number of reasoning hops required (typically 2-4 for this dataset)
+- **hpqa_id** (`string`): Original HotpotQA question ID from which the claim was derived
 
 ### Data Splits
 
-[More Information Needed]
+| Split | Examples |
+|-------|----------|
+| Train | 18,171 |
+| Validation | 4,000 |
+| Test | 4,000 |
+| **Total** | **26,171** |
+
+The splits maintain the original distribution from the HoVer dataset.
 
 ## Dataset Creation
 
 ### Curation Rationale
 
-[More Information Needed]
+HoVer was created to address the challenge of multi-hop fact verification, where claims require reasoning across multiple documents. The dataset was built to push the boundaries of claim verification systems beyond single-document fact-checking.
 
 ### Source Data
 
-[More Information Needed]
-
-#### Initial Data Collection and Normalization
-
-[More Information Needed]
-
-#### Who are the source language producers?
-
-[More Information Needed]
+The dataset is built upon Wikipedia as the knowledge source. Claims are adapted from HotpotQA question-answer pairs and modified to create verification statements that require multi-hop reasoning.
 
 ### Annotations
 
-[More Information Needed]
-
-#### Annotation process
-
-[More Information Needed]
-
-#### Who are the annotators?
-
-[More Information Needed]
-
-### Personal and Sensitive Information
-
-[More Information Needed]
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed]
-
-### Discussion of Biases
-
-[More Information Needed]
-
-### Other Known Limitations
-
-[More Information Needed]
+The dataset was annotated by expert annotators who identified supporting facts across multiple Wikipedia articles and determined whether claims were supported or not supported by the evidence.
 
 ## Additional Information
 
-### Dataset Curators
-
-[More Information Needed]
-
 ### Licensing Information
 
-[More Information Needed]
+This dataset is licensed under CC-BY-SA 4.0 (Creative Commons Attribution-ShareAlike 4.0 International).
 
 ### Citation Information
 
-[More Information Needed]
+```bibtex
+@inproceedings{jiang2020hover,
+  title={{HoVer}: A Dataset for Many-Hop Fact Extraction And Claim Verification},
+  author={Yichen Jiang and Shikha Bordia and Zheng Zhong and Charles Dognin and Maneesh Singh and Mohit Bansal},
+  booktitle={Findings of the Conference on Empirical Methods in Natural Language Processing (EMNLP)},
+  year={2020}
+}
+```
+
 ### Contributions
 
-Thanks to [@abhishekkrthakur](https://github.com/abhishekkrthakur) for adding this dataset.
+Thanks to [@abhishekkrthakur](https://github.com/abhishekkrthakur) for adding the original dataset and [@vincentkoc](https://github.com/vincentkoc) for creating this Parquet version.