Sefika's picture
Update README.md
8169393 verified
|
raw
history blame
3.73 kB
metadata
license: mit
task_categories:
  - text-classification
  - text-generation
language:
  - en
pretty_name: Relation Extraction for Inverse Relations FewRel
size_categories:
  - 1K<n<10K
tags:
  - relation-extraction
  - nlp
  - dataset-robustness
  - inverse-relations

Reversing Arrows: A Benchmark Dataset for Inverse Relation Directionality in LLMs

This dataset is designed to evaluate the robustness of Relation Extraction (RE) models, with a specific focus on Inverse Relations and entity substitution. It is derived from FewRel. The croissant metadata is available on croissant

Dataset Summary

The primary goal of this dataset is to test whether models can recognize a relationship regardless of the direction or the surface form of the entities. It includes:

  1. Inverse Mapping: Every sample includes both the forward relation (e.g., Mother) and its logical inverse (e.g., Child). -- Original data : original_fewrel_inverse.json
  2. Synthetics Substitutions: A version of the dataset where real-world entities are replaced with synthetic names (e.g., replacing "Denmark" with "Emilyfort") to test if models rely on memorized entity knowledge rather than linguistic context. -- synthetic_fewrel_inverse.json

Relation Examples

Forward Relation Inverse Relation
Child (P40) Mother (P25)
Child (P40) Father (P22)
Follows (P155) Followed by (P156)
Has Part (P527) Part of (P361)

Dataset Structure

The dataset is provided in JSON format and split into four main distributions:

  • Original FewRel: The ground-truth sentences and relations. (original_fewrel_inverse.json)
  • Synthetic FewRel: Sentences where entities have been substituted with synthetic placeholders. (synthetic_fewrel_inverse.json)
  • Relation Metadata: Supplemental files providing human-readable definitions for Wikidata P-IDs (fewrel_inverse_relations.json)

Key Fields

  • tokens: The input text (tokenized or raw string) in FewRel.
  • head / tail: The subject and object entities.
  • head_to_tail: The ID/Name of the forward relation.
  • tail_to_head: The ID/Name of the inverse relation.
  • artificial_data: A mapping showing which Original entities were changed to which Synthetic placeholders.

Usage

You can load this dataset for tasks such as:

  • Text Classification: Predicting the relation ID between two entities.
  • Text Generation: Generating a sentence that expresses a specific inverse relation.

Repository

For scripts and more technical details on how the artificial data was generated, visit the official repository: sefeoglu/inverserelations

Citation

If you use this dataset in your research, please cite the original FewRel and this repository.


@misc{fewrel_inverse_2025,
  author = {Sefika Efeoglu, and Adrian Paschke},
  title = { Reversing Arrows: A Benchmark Dataset for Inverse Relation Directionality in LLMs},
  year = {2025},
  publisher = {GitHub/HuggingFace},
  doi = { 10.57967/hf/8462 },
  howpublished = {https://github.com/sefeoglu/inverserelations}
}