---
license: cc-by-4.0
language:
  - en
task_categories:
  - text-classification
  - other
pretty_name: CondRelBench
size_categories:
  - 10K<n<100K
tags:
  - conditional-relations
  - relation-extraction
  - natural-language-inference
---

# CondRelBench

CondRelBench is a mixed-domain benchmark for condition-scoped relation
understanding. It contains extraction data and handcrafted P1–P5 probe families
from Synthetic, PubMed, and Reddit domains.

Dataset record: [https://doi.org/10.6084/m9.figshare.32948507](https://doi.org/10.6084/m9.figshare.32948507)

Code and evaluation repository:
[sydneyanuyah/ConditionalCausality](https://github.com/sydneyanuyah/ConditionalCausality)

## Dataset contents

| Path | Contents |
|---|---|
| `data/extraction/` | Gold condition-scoped extraction data |
| `data/probes/` | Canonical P1–P5 probe tables and gold labels |
| `data/splits/extraction/` | Extraction train, validation, and test splits |
| `data/splits/probes/` | Probe train, validation, and test splits |

The canonical probe files contain 52,112 rows grouped into 10,449 tuple families.

## Probe structure

Each condition-scoped tuple has five intended probe claims:

| Probe | Transformation | Gold label |
|---|---|---|
| P1 | Contradict the relation | Not Supported |
| P2 | Replace the condition | Not Enough Evidence |
| P3 | Remove the condition | Not Enough Evidence |
| P4 | Preserve the original condition-scoped relation | Supported |
| P5 | Contradict the condition | Not Supported |

`Tuple_ID` identifies the probe family, and `ProbeID` identifies an individual
claim. Labels describe whether the complete claim is licensed by the supplied
paragraph.

## Included documentation

- `data_dictionary.md`
- `split_protocol.md`
- `probe_construction.md`
- `annotation_and_boundary_rules.md`
- `CITATION.md`
- `LICENSE_DATA.md`

## Citation

Please cite **CondRelBench: A Mixed-Domain Benchmark for Condition-Scoped Relation
Understanding** and the dataset DOI. See `CITATION.md` for the current citation
record.

## License

The dataset is distributed under Creative Commons Attribution 4.0 International
(CC BY 4.0). See `LICENSE_DATA.md`.