Datasets:

DFKI-SLT
/

few-nerd

	---
	annotations_creators:
	- expert-generated
	language_creators:
	- found
	language:
	- en
	license:
	- cc-by-sa-4.0
	multilinguality:
	- monolingual
	size_categories:
	- 100K<n<1M
	source_datasets:
	- extended\|wikipedia
	task_categories:
	- token-classification
	task_ids:
	- named-entity-recognition
	paperswithcode_id: few-nerd
	pretty_name: Few-NERD
	tags:
	- structure-prediction
	dataset_info:
	- config_name: inter
	features:
	- name: id
	dtype: string
	- name: tokens
	sequence: string
	- name: ner_tags
	sequence:
	class_label:
	names:
	'0': O
	'1': art
	'2': building
	'3': event
	'4': location
	'5': organization
	'6': other
	'7': person
	'8': product
	- name: fine_ner_tags
	sequence:
	class_label:
	names:
	'0': O
	'1': art-broadcastprogram
	'2': art-film
	'3': art-music
	'4': art-other
	'5': art-painting
	'6': art-writtenart
	'7': building-airport
	'8': building-hospital
	'9': building-hotel
	'10': building-library
	'11': building-other
	'12': building-restaurant
	'13': building-sportsfacility
	'14': building-theater
	'15': event-attack/battle/war/militaryconflict
	'16': event-disaster
	'17': event-election
	'18': event-other
	'19': event-protest
	'20': event-sportsevent
	'21': location-GPE
	'22': location-bodiesofwater
	'23': location-island
	'24': location-mountain
	'25': location-other
	'26': location-park
	'27': location-road/railway/highway/transit
	'28': organization-company
	'29': organization-education
	'30': organization-government/governmentagency
	'31': organization-media/newspaper
	'32': organization-other
	'33': organization-politicalparty
	'34': organization-religion
	'35': organization-showorganization
	'36': organization-sportsleague
	'37': organization-sportsteam
	'38': other-astronomything
	'39': other-award
	'40': other-biologything
	'41': other-chemicalthing
	'42': other-currency
	'43': other-disease
	'44': other-educationaldegree
	'45': other-god
	'46': other-language
	'47': other-law
	'48': other-livingthing
	'49': other-medical
	'50': person-actor
	'51': person-artist/author
	'52': person-athlete
	'53': person-director
	'54': person-other
	'55': person-politician
	'56': person-scholar
	'57': person-soldier
	'58': product-airplane
	'59': product-car
	'60': product-food
	'61': product-game
	'62': product-other
	'63': product-ship
	'64': product-software
	'65': product-train
	'66': product-weapon
	splits:
	- name: train
	num_bytes: 87456461
	num_examples: 130112
	- name: validation
	num_bytes: 10813084
	num_examples: 18817
	- name: test
	num_bytes: 7920453
	num_examples: 14007
	download_size: 19914244
	dataset_size: 106189998
	- config_name: intra
	features:
	- name: id
	dtype: string
	- name: tokens
	sequence: string
	- name: ner_tags
	sequence:
	class_label:
	names:
	'0': O
	'1': art
	'2': building
	'3': event
	'4': location
	'5': organization
	'6': other
	'7': person
	'8': product
	- name: fine_ner_tags
	sequence:
	class_label:
	names:
	'0': O
	'1': art-broadcastprogram
	'2': art-film
	'3': art-music
	'4': art-other
	'5': art-painting
	'6': art-writtenart
	'7': building-airport
	'8': building-hospital
	'9': building-hotel
	'10': building-library
	'11': building-other
	'12': building-restaurant
	'13': building-sportsfacility
	'14': building-theater
	'15': event-attack/battle/war/militaryconflict
	'16': event-disaster
	'17': event-election
	'18': event-other
	'19': event-protest
	'20': event-sportsevent
	'21': location-GPE
	'22': location-bodiesofwater
	'23': location-island
	'24': location-mountain
	'25': location-other
	'26': location-park
	'27': location-road/railway/highway/transit
	'28': organization-company
	'29': organization-education
	'30': organization-government/governmentagency
	'31': organization-media/newspaper
	'32': organization-other
	'33': organization-politicalparty
	'34': organization-religion
	'35': organization-showorganization
	'36': organization-sportsleague
	'37': organization-sportsteam
	'38': other-astronomything
	'39': other-award
	'40': other-biologything
	'41': other-chemicalthing
	'42': other-currency
	'43': other-disease
	'44': other-educationaldegree
	'45': other-god
	'46': other-language
	'47': other-law
	'48': other-livingthing
	'49': other-medical
	'50': person-actor
	'51': person-artist/author
	'52': person-athlete
	'53': person-director
	'54': person-other
	'55': person-politician
	'56': person-scholar
	'57': person-soldier
	'58': product-airplane
	'59': product-car
	'60': product-food
	'61': product-game
	'62': product-other
	'63': product-ship
	'64': product-software
	'65': product-train
	'66': product-weapon
	splits:
	- name: train
	num_bytes: 67631522
	num_examples: 99519
	- name: validation
	num_bytes: 12759787
	num_examples: 19358
	- name: test
	num_bytes: 25768577
	num_examples: 44059
	download_size: 19616006
	dataset_size: 106159886
	- config_name: supervised
	features:
	- name: id
	dtype: string
	- name: tokens
	sequence: string
	- name: ner_tags
	sequence:
	class_label:
	names:
	'0': O
	'1': art
	'2': building
	'3': event
	'4': location
	'5': organization
	'6': other
	'7': person
	'8': product
	- name: fine_ner_tags
	sequence:
	class_label:
	names:
	'0': O
	'1': art-broadcastprogram
	'2': art-film
	'3': art-music
	'4': art-other
	'5': art-painting
	'6': art-writtenart
	'7': building-airport
	'8': building-hospital
	'9': building-hotel
	'10': building-library
	'11': building-other
	'12': building-restaurant
	'13': building-sportsfacility
	'14': building-theater
	'15': event-attack/battle/war/militaryconflict
	'16': event-disaster
	'17': event-election
	'18': event-other
	'19': event-protest
	'20': event-sportsevent
	'21': location-GPE
	'22': location-bodiesofwater
	'23': location-island
	'24': location-mountain
	'25': location-other
	'26': location-park
	'27': location-road/railway/highway/transit
	'28': organization-company
	'29': organization-education
	'30': organization-government/governmentagency
	'31': organization-media/newspaper
	'32': organization-other
	'33': organization-politicalparty
	'34': organization-religion
	'35': organization-showorganization
	'36': organization-sportsleague
	'37': organization-sportsteam
	'38': other-astronomything
	'39': other-award
	'40': other-biologything
	'41': other-chemicalthing
	'42': other-currency
	'43': other-disease
	'44': other-educationaldegree
	'45': other-god
	'46': other-language
	'47': other-law
	'48': other-livingthing
	'49': other-medical
	'50': person-actor
	'51': person-artist/author
	'52': person-athlete
	'53': person-director
	'54': person-other
	'55': person-politician
	'56': person-scholar
	'57': person-soldier
	'58': product-airplane
	'59': product-car
	'60': product-food
	'61': product-game
	'62': product-other
	'63': product-ship
	'64': product-software
	'65': product-train
	'66': product-weapon
	splits:
	- name: train
	num_bytes: 81848645
	num_examples: 131767
	- name: validation
	num_bytes: 11731110
	num_examples: 18824
	- name: test
	num_bytes: 23345314
	num_examples: 37648
	download_size: 24121858
	dataset_size: 116925069
	configs:
	- config_name: inter
	data_files:
	- split: train
	path: inter/train-*
	- split: validation
	path: inter/validation-*
	- split: test
	path: inter/test-*
	- config_name: intra
	data_files:
	- split: train
	path: intra/train-*
	- split: validation
	path: intra/validation-*
	- split: test
	path: intra/test-*
	- config_name: supervised
	data_files:
	- split: train
	path: supervised/train-*
	- split: validation
	path: supervised/validation-*
	- split: test
	path: supervised/test-*
	---

	# Dataset Card for "Few-NERD"

	## Table of Contents
	- [Dataset Description](
	#dataset-description)
	- [Dataset Summary](#dataset-summary)
	- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
	- [Languages](#languages)
	- [Dataset Structure](#dataset-structure)
	- [Data Instances](#data-instances)
	- [Data Fields](#data-fields)
	- [Data Splits](#data-splits)
	- [Dataset Creation](#dataset-creation)
	- [Curation Rationale](#curation-rationale)
	- [Source Data](#source-data)
	- [Annotations](#annotations)
	- [Personal and Sensitive Information](#personal-and-sensitive-information)
	- [Considerations for Using the Data](#considerations-for-using-the-data)
	- [Social Impact of Dataset](#social-impact-of-dataset)
	- [Discussion of Biases](#discussion-of-biases)
	- [Other Known Limitations](#other-known-limitations)
	- [Additional Information](#additional-information)
	- [Dataset Curators](#dataset-curators)
	- [Licensing Information](#licensing-information)
	- [Citation Information](#citation-information)
	- [Contributions](#contributions)

	## Dataset Description

	- Homepage: [https://ningding97.github.io/fewnerd/](https://ningding97.github.io/fewnerd/)
	- Repository: [https://github.com/thunlp/Few-NERD](https://github.com/thunlp/Few-NERD)
	- Paper: [https://aclanthology.org/2021.acl-long.248/](https://aclanthology.org/2021.acl-long.248/)
	- Point of Contact: See [https://ningding97.github.io/fewnerd/](https://ningding97.github.io/fewnerd/)

	### Dataset Summary

	This script is for loading the Few-NERD dataset from https://ningding97.github.io/fewnerd/.

	Few-NERD is a large-scale, fine-grained manually annotated named entity recognition dataset, which contains 8 coarse-grained types, 66 fine-grained types, 188,200 sentences, 491,711 entities, and 4,601,223 tokens. Three benchmark tasks are built, one is supervised (Few-NERD (SUP)) and the other two are few-shot (Few-NERD (INTRA) and Few-NERD (INTER)).

	NER tags use the `IO` tagging scheme. The original data uses a 2-column CoNLL-style format, with empty lines to separate sentences. DOCSTART information is not provided since the sentences are randomly ordered.

	For more details see https://ningding97.github.io/fewnerd/ and https://aclanthology.org/2021.acl-long.248/.

	### Supported Tasks and Leaderboards

	- Tasks: Named Entity Recognition, Few-shot NER
	- Leaderboards:
	- https://ningding97.github.io/fewnerd/
	- named-entity-recognition:https://paperswithcode.com/sota/named-entity-recognition-on-few-nerd-sup
	- other-few-shot-ner:https://paperswithcode.com/sota/few-shot-ner-on-few-nerd-intra
	- other-few-shot-ner:https://paperswithcode.com/sota/few-shot-ner-on-few-nerd-inter


	### Languages

	English

	## Dataset Structure

	### Data Instances

	- Size of downloaded dataset files:
	- `super`: 14.6 MB
	- `intra`: 11.4 MB
	- `inter`: 11.5 MB

	- Size of the generated dataset:
	- `super`: 116.9 MB
	- `intra`: 106.2 MB
	- `inter`: 106.2 MB

	- Total amount of disk used: 366.8 MB


	An example of 'train' looks as follows.

	```json
	{
	'id': '1',
	'tokens': ['It', 'starred', 'Hicks', "'s", 'wife', ',', 'Ellaline', 'Terriss', 'and', 'Edmund', 'Payne', '.'],
	'ner_tags': [0, 0, 7, 0, 0, 0, 7, 7, 0, 7, 7, 0],
	'fine_ner_tags': [0, 0, 51, 0, 0, 0, 50, 50, 0, 50, 50, 0]
	}
	```



	### Data Fields

	The data fields are the same among all splits.

	- `id`: a `string` feature.
	- `tokens`: a `list` of `string` features.
	- `ner_tags`: a `list` of classification labels, with possible values including `O` (0), `art` (1), `building` (2), `event` (3), `location` (4), `organization` (5), `other`(6), `person` (7), `product` (8)
	- `fine_ner_tags`: a `list` of fine-grained classification labels, with possible values including `O` (0), `art-broadcastprogram` (1), `art-film` (2), ...

	### Data Splits

	\| Task \| Train \| Dev \| Test \|
	\| ----- \| ------ \| ----- \| ---- \|
	\| SUP \| 131767 \| 18824 \| 37648 \|
	\| INTRA \| 99519 \| 19358 \| 44059 \|
	\| INTER \| 130112 \| 18817 \| 14007 \|

	## Dataset Creation

	### Curation Rationale

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Source Data

	#### Initial Data Collection and Normalization

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	#### Who are the source language producers?

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Annotations

	#### Annotation process

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	#### Who are the annotators?

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Personal and Sensitive Information

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	## Considerations for Using the Data

	### Social Impact of Dataset

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Discussion of Biases

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Other Known Limitations

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	## Additional Information

	### Dataset Curators

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Licensing Information

	[CC BY-SA 4.0 license](https://creativecommons.org/licenses/by-sa/4.0/)

	### Citation Information

	```
	@inproceedings{ding-etal-2021-nerd,
	title = "Few-{NERD}: A Few-shot Named Entity Recognition Dataset",
	author = "Ding, Ning and
	Xu, Guangwei and
	Chen, Yulin and
	Wang, Xiaobin and
	Han, Xu and
	Xie, Pengjun and
	Zheng, Haitao and
	Liu, Zhiyuan",
	booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
	month = aug,
	year = "2021",
	address = "Online",
	publisher = "Association for Computational Linguistics",
	url = "https://aclanthology.org/2021.acl-long.248",
	doi = "10.18653/v1/2021.acl-long.248",
	pages = "3198--3213",
	}
	```


	### Contributions