metadata
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- n<1K
pretty_name: ConceptNet with High Confidence
Dataset Card for "relbert/conceptnet_relation_similarity"
Dataset Description
- Repository: RelBERT
- Paper: https://home.ttic.edu/~kgimpel/commonsense.html
- Dataset: Relational similarity dataset based on the high-confidence subset of ConceptNet
Dataset Summary
The selected subset of ConceptNet used in this work, which compiled
to fine-tune RelBERT model.
We removed NotCapableOf and NotDesires to keep the positive relation only.
We consider the original test set as test set, dev1 as the training set, and dev2 as the validation set.
Dataset Structure
Data Instances
An example of train looks as follows.
{
"relation_type": "AtLocation",
"positives": [["fish", "water"], ["cloud", "sky"], ["child", "school"], ... ],
"negatives": [["pen", "write"], ["sex", "fun"], ["soccer", "sport"], ["fish", "school"], ... ]
}
Data Splits
| train | validation | test |
|---|---|---|
| 28 | 34 | 16 |
Citation Information
@InProceedings{P16-1137,
author = "Li, Xiang
and Taheri, Aynaz
and Tu, Lifu
and Gimpel, Kevin",
title = "Commonsense Knowledge Base Completion",
booktitle = "Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) ",
year = "2016",
publisher = "Association for Computational Linguistics",
pages = "1445--1455",
location = "Berlin, Germany",
doi = "10.18653/v1/P16-1137",
url = "http://aclweb.org/anthology/P16-1137"
}