Dataset Card for "relbert/conceptnet_high_confidence"

Dataset Summary

The selected subset of ConceptNet used in this work, which compiled to fine-tune RelBERT model.

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

name	train	validation
conceptnet_high_confidence	25	24

Number of Positive/Negative Word-pairs in each Split

relation_type	positive (train)	negative (train)	positive (validation)	negative (validation)
AtLocation	383	1768	97	578
CapableOf	195	1790	73	600
Causes	71	1797	26	595
CausesDesire	9	1793	11	595
CreatedBy	2	1796	0	0
DefinedAs	0	0	2	595
Desires	16	1794	12	595
HasA	67	1814	17	595
HasFirstSubevent	2	1796	0	0
HasLastSubevent	2	1796	3	593
HasPrerequisite	168	1803	57	592
HasProperty	94	1801	39	605
HasSubevent	125	1798	40	609
IsA	310	1764	98	603
MadeOf	17	1793	7	593
MotivatedByGoal	14	1796	11	595
NotCapableOf	15	1793	0	0
NotDesires	4	1795	4	592
PartOf	34	1801	7	593
ReceivesAction	18	1793	8	593
SymbolOf	0	0	2	596
UsedFor	249	1815	81	588
SUM	1795	35896	595	11305

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"
}