annotations_creators:
- crowdsourced
- machine-generated
language_creators:
- found
language:
- en
license:
- mit
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
- n<1K
source_datasets:
- original
task_categories:
- other
task_ids: []
paperswithcode_id: fewrel
pretty_name: Few-Shot Relation Classification Dataset
tags:
- relation-extraction
dataset_info:
- config_name: default
features:
- name: relation
dtype: string
- name: tokens
sequence: string
- name: head
struct:
- name: text
dtype: string
- name: type
dtype: string
- name: indices
sequence:
sequence: int64
- name: tail
struct:
- name: text
dtype: string
- name: type
dtype: string
- name: indices
sequence:
sequence: int64
- name: names
sequence: string
splits:
- name: train_wiki
num_bytes: 19923155
num_examples: 44800
- name: val_nyt
num_bytes: 1385642
num_examples: 2500
- name: val_pubmed
num_bytes: 488502
num_examples: 1000
- name: val_semeval
num_bytes: 2646249
num_examples: 8851
- name: val_wiki
num_bytes: 5147348
num_examples: 11200
- name: pubmed_unsupervised
num_bytes: 1117703
num_examples: 2500
download_size: 22674323
dataset_size: 30708599
- config_name: pid2name
features:
- name: relation
dtype: string
- name: names
sequence: string
splits:
- name: pid2name
num_bytes: 81607
num_examples: 744
download_size: 22674323
dataset_size: 81607
config_names:
- default
- pid2name
Dataset Card for few_rel
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: GitHub Page
- Repository: GitHub
- Paper: FewRel, FewRel 2.0
- Leaderboard: GitHub Leaderboard
- Point of Contact: [Needs More Information]
Dataset Summary
FewRel is a large-scale few-shot relation extraction dataset, which contains more than one hundred relations and tens of thousands of annotated instances cross different domains.
Supported Tasks and Leaderboards
[Needs More Information]
Languages
The dataset contaings English text, as used by writers on Wikipedia, and crowdsourced English annotations.
Dataset Structure
Data Instances
An instance from train_wiki
split:
{'head': {'indices': [[16]], 'text': 'tjq', 'type': 'Q1331049'}, 'names': ['place served by transport hub', 'territorial entity or entities served by this transport hub (airport, train station, etc.)'], 'relation': 'P931', 'tail': {'indices': [[13, 14]], 'text': 'tanjung pandan', 'type': 'Q3056359'}, 'tokens': ['Merpati', 'flight', '106', 'departed', 'Jakarta', '(', 'CGK', ')', 'on', 'a', 'domestic', 'flight', 'to', 'Tanjung', 'Pandan', '(', 'TJQ', ')', '.']}
Data Fields
For default
:
relation
: astring
feature containing PID of the relation.tokens
: alist
ofstring
features containing tokens for the text.head
: a dictionary containing:text
: astring
feature representing the head entity.type
: astring
feature representing the type of the head entity.indices
: alist
containinglist
of token indices.
tail
: a dictionary containing:text
: astring
feature representing the tail entity.type
: astring
feature representing the type of the tail entity.indices
: alist
containinglist
of token indices.
names
: alist
ofstring
features containing relation names. Forpubmed_unsupervised
split, this is set to alist
with an emptystring
. Forval_semeval
andval_pubmed
split, this is set to alist
with thestring
from therelation
field.
Data Splits
train_wiki
: 44800
val_nyt
: 2500
val_pubmed
: 1000
val_semeval
: 8851
val_wiki
: 11200
pubmed_unsupervised
: 2500
Dataset Creation
Curation Rationale
[Needs More Information]
Source Data
Initial Data Collection and Normalization
[Needs More Information]
Who are the source language producers?
[Needs More Information]
Annotations
Annotation process
[Needs More Information]
Who are the annotators?
[Needs More Information]
Personal and Sensitive Information
[Needs More Information]
Considerations for Using the Data
Social Impact of Dataset
[Needs More Information]
Discussion of Biases
[Needs More Information]
Other Known Limitations
[Needs More Information]
Additional Information
Dataset Curators
For FewRel:
Han, Xu and Zhu, Hao and Yu, Pengfei and Wang, Ziyun and Yao, Yuan and Liu, Zhiyuan and Sun, Maosong
For FewRel 2.0:
Gao, Tianyu and Han, Xu and Zhu, Hao and Liu, Zhiyuan and Li, Peng and Sun, Maosong and Zhou, Jie
Licensing Information
MIT License
Copyright (c) 2018 THUNLP
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Citation Information
@inproceedings{han-etal-2018-fewrel,
title = "{F}ew{R}el: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation",
author = "Han, Xu and Zhu, Hao and Yu, Pengfei and Wang, Ziyun and Yao, Yuan and Liu, Zhiyuan and Sun, Maosong",
booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing",
month = oct # "-" # nov,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/D18-1514",
doi = "10.18653/v1/D18-1514",
pages = "4803--4809"
}
@inproceedings{gao-etal-2019-fewrel,
title = "{F}ew{R}el 2.0: Towards More Challenging Few-Shot Relation Classification",
author = "Gao, Tianyu and Han, Xu and Zhu, Hao and Liu, Zhiyuan and Li, Peng and Sun, Maosong and Zhou, Jie",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/D19-1649",
doi = "10.18653/v1/D19-1649",
pages = "6251--6256"
}
Contributions
Thanks to @gchhablani for adding this dataset.