
# Dataset Card for "relbert/conceptnet_relation_similarity"
## Dataset Description
- **Repository:** [RelBERT](https://github.com/asahi417/relbert)
- **Paper:** [https://home.ttic.edu/~kgimpel/commonsense.html](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](https://home.ttic.edu/~kgimpel/commonsense.html), which compiled 
to fine-tune [RelBERT](https://github.com/asahi417/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.
```shell
{
    "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"
}
```
multilinguality:monolingual size_categories:n<1K language:en license:other region:us
{"language": ["en"], "license": ["other"], "multilinguality": ["monolingual"], "size_categories": ["n<1K"], "pretty_name": "ConceptNet with High Confidence"}
TAGS
#multilinguality-monolingual #size_categories-n<1K #language-English #license-other #region-us 

Dataset Card for "relbert/conceptnet\_relation\_similarity"
===========================================================


Dataset Description
-------------------


* Repository: RelBERT
* Paper: URL
* 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.


### Data Splits




### 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. ### Data Splits
TAGS
#multilinguality-monolingual #size_categories-n<1K #language-English #license-other #region-us 
 ### 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. ### Data Splits
passage: TAGS
#multilinguality-monolingual #size_categories-n<1K #language-English #license-other #region-us 
### 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.### Data Splits