| --- |
| language: |
| - en |
| task_categories: |
| - question-answering |
| tags: |
| - procedural-reasoning |
| - rule-reasoning |
| - retrieval |
| - synthetic-data |
| - large-language-models |
| pretty_name: RuleWorld |
| size_categories: |
| - 1M<n<10M |
|
|
| --- |
| |
| # RuleWorld |
|
|
| RuleWorld is a large-scale benchmark for evaluating whether language models can retrieve and apply a shared repository of externally provided procedural rules. Its rules are abstract, globally reusable, and intentionally non-commonsense, so a model cannot answer reliably from world knowledge alone. Each rule is supplied in aligned natural-language (NL) and first-order logic (FOL) forms. |
|
|
| The benchmark covers three reasoning settings: Single-Rule QA, Parallel Multi-Rule QA, and Multi-Hop QA. Parallel questions combine independent sub-questions, while multi-hop questions require sequential rule application. |
|
|
| <table> |
| <tr> |
| <td width="70%" align="center"><img src="assets/benchmark.png" alt="RuleWorld overview" width="100%"></td> |
| <td width="30%" align="center"><img src="assets/qa_type_statistics_with_rules.png" alt="QA and rule statistics" width="100%"></td> |
| </tr> |
| </table> |
| |
| ## Dataset summary |
|
|
|
|
| | Resource | Records | Description | |
| | ----------------------- | --------- | ---------------------------------------------------------------------------------- | |
| | Rule library | 4,936,113 | Globally shared procedural rules, each in NL and FOL forms. | |
| | Full QA collection | 3,377,737 | 50,000 Single-Rule, 3,250,000 Parallel Multi-Rule, and 77,737 Multi-Hop instances. | |
| | Training split | 111,200 | 25,000 Single-Rule, 49,200 Parallel Multi-Rule, and 37,000 Multi-Hop instances. | |
| | Development split | 3,390 | Development instances. | |
| | Official evaluation set | 550 | The evaluation split: 550 instances. | |
|
|
|
|
| The full QA collection contains eleven fine-grained subtasks: `single-rule`, `multi-rule-2` through `multi-rule-8`, and `multi-hop-2` through `multi-hop-4`. For Multi-Rule QA, the numeric suffix denotes the number of distinct gold rules (with a minimum label of 2); for Multi-Hop QA, it denotes the reasoning depth. |
|
|
| ## Repository layout |
|
|
| ```text |
| all_data/ |
| rule_library.txt # Full rule library; recommended rule source |
| rule_library.pkl # Serialized generation-time representation |
| single_qa.jsonl # 50,000 Single-Rule QA instances |
| multi_qa_base.jsonl # 30,000 base Multi-Rule QA instances |
| multi_qa_generated_{2,3,4}.jsonl # 3,220,000 composed Parallel Multi-Rule instances |
| multi_hop_qa.jsonl # 77,737 Multi-Hop QA instances |
| sampled/ |
| train_111200.jsonl # Training split |
| dev_3390.jsonl # Development split |
| verified/ |
| test_550.jsonl # Official balanced evaluation set |
| ``` |
|
|
| `all_data/rule_library.txt` is tab-separated with the columns `rule_id`, `natural_language_rule`, `fol_rule`, and `rule_type`. Use this text file rather than the pickle file when portability and security matter. |
|
|
| ## QA format |
|
|
| Every QA instance is a JSON object. Core fields are: |
|
|
|
|
| | Field | Description | |
| | ------------ | ------------------------------------------------------------------------------------- | |
| | `id` | Unique QA identifier. | |
| | `Q` | Natural-language question. | |
| | `A` | Gold answer list, ordered to match the question or its sub-questions. | |
| | `Q_template` | Prompt template containing the `{rules}` and `{question}` placeholders. | |
| | `A_template` | Reference answer template. After formatting, the answer is enclosed in `\boxed{...}`. | |
| | `proofs` | Gold derivation steps. Integer entries are rule IDs from the rule library. | |
| | `rule_info` | Structured gold rule metadata used for retrieval supervision. | |
| | `task_type` | One of `single_rule`, `multi_rule`, or `multi_hop`. | |
| | `qa_type` | Underlying rule subtype(s) involved in the instance. | |
|
|
|
|
| `multi_rule` records additionally contain `rule_width`, and `multi_hop` records contain `rule_depth`. Composed Multi-Rule records include `source_ids`, which preserve the order of their component QA instances. The official evaluation set also stores `final_qa_type`, `selection_seed`, and `subtask`. |
|
|
| ## Citation |
|
|
| If you find this dataset helpful in your research, we would kindly appreciate a citation: |
|
|
| ```bibtex |
| @misc{yu2026factualknowledgebenchmarkinglearning, |
| title={Beyond Factual Knowledge: Benchmarking and Learning Step-Level Procedural Rule Reasoning in Large Language Models}, |
| author={Bohan Yu and Pengfei Cao and Chen Han and Chenxi Zhou and Zhiheng Zhang and Zhiyang Xie and Wenhao Teng and Xiangwen Liao and Jun Zhao and Kang Liu}, |
| year={2026}, |
| eprint={2608.22753}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CL}, |
| url={https://arxiv.org/abs/2608.22753}, |
| } |
| ``` |
|
|
