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"
}