Datasets:

CogComp
/

trec

	---
	annotations_creators:
	- expert-generated
	language_creators:
	- expert-generated
	language:
	- en
	license:
	- unknown
	multilinguality:
	- monolingual
	size_categories:
	- 1K<n<10K
	source_datasets:
	- original
	task_categories:
	- text-classification
	task_ids:
	- multi-class-classification
	paperswithcode_id: trecqa
	pretty_name: Text Retrieval Conference Question Answering
	dataset_info:
	features:
	- name: text
	dtype: string
	- name: coarse_label
	dtype:
	class_label:
	names:
	'0': ABBR
	'1': ENTY
	'2': DESC
	'3': HUM
	'4': LOC
	'5': NUM
	- name: fine_label
	dtype:
	class_label:
	names:
	'0': ABBR:abb
	'1': ABBR:exp
	'2': ENTY:animal
	'3': ENTY:body
	'4': ENTY:color
	'5': ENTY:cremat
	'6': ENTY:currency
	'7': ENTY:dismed
	'8': ENTY:event
	'9': ENTY:food
	'10': ENTY:instru
	'11': ENTY:lang
	'12': ENTY:letter
	'13': ENTY:other
	'14': ENTY:plant
	'15': ENTY:product
	'16': ENTY:religion
	'17': ENTY:sport
	'18': ENTY:substance
	'19': ENTY:symbol
	'20': ENTY:techmeth
	'21': ENTY:termeq
	'22': ENTY:veh
	'23': ENTY:word
	'24': DESC:def
	'25': DESC:desc
	'26': DESC:manner
	'27': DESC:reason
	'28': HUM:gr
	'29': HUM:ind
	'30': HUM:title
	'31': HUM:desc
	'32': LOC:city
	'33': LOC:country
	'34': LOC:mount
	'35': LOC:other
	'36': LOC:state
	'37': NUM:code
	'38': NUM:count
	'39': NUM:date
	'40': NUM:dist
	'41': NUM:money
	'42': NUM:ord
	'43': NUM:other
	'44': NUM:period
	'45': NUM:perc
	'46': NUM:speed
	'47': NUM:temp
	'48': NUM:volsize
	'49': NUM:weight
	splits:
	- name: train
	num_bytes: 385090
	num_examples: 5452
	- name: test
	num_bytes: 27983
	num_examples: 500
	download_size: 359212
	dataset_size: 413073
	---

	# Dataset Card for "trec"

	## 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://cogcomp.seas.upenn.edu/Data/QA/QC/](https://cogcomp.seas.upenn.edu/Data/QA/QC/)
	- Repository: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
	- Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
	- Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
	- Size of downloaded dataset files: 0.36 MB
	- Size of the generated dataset: 0.41 MB
	- Total amount of disk used: 0.78 MB

	### Dataset Summary

	The Text REtrieval Conference (TREC) Question Classification dataset contains 5500 labeled questions in training set and another 500 for test set.

	The dataset has 6 coarse class labels and 50 fine class labels. Average length of each sentence is 10, vocabulary size of 8700.

	Data are collected from four sources: 4,500 English questions published by USC (Hovy et al., 2001), about 500 manually constructed questions for a few rare classes, 894 TREC 8 and TREC 9 questions, and also 500 questions from TREC 10 which serves as the test set. These questions were manually labeled.

	### Supported Tasks and Leaderboards

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

	### Languages

	The language in this dataset is English (`en`).

	## Dataset Structure

	### Data Instances

	- Size of downloaded dataset files: 0.36 MB
	- Size of the generated dataset: 0.41 MB
	- Total amount of disk used: 0.78 MB

	An example of 'train' looks as follows.
	```
	{
	'text': 'How did serfdom develop in and then leave Russia ?',
	'coarse_label': 2,
	'fine_label': 26
	}
	```

	### Data Fields

	The data fields are the same among all splits.

	- `text` (`str`): Text of the question.
	- `coarse_label` (`ClassLabel`): Coarse class label. Possible values are:
	- 'ABBR' (0): Abbreviation.
	- 'ENTY' (1): Entity.
	- 'DESC' (2): Description and abstract concept.
	- 'HUM' (3): Human being.
	- 'LOC' (4): Location.
	- 'NUM' (5): Numeric value.
	- `fine_label` (`ClassLabel`): Fine class label. Possible values are:
	- ABBREVIATION:
	- 'ABBR:abb' (0): Abbreviation.
	- 'ABBR:exp' (1): Expression abbreviated.
	- ENTITY:
	- 'ENTY:animal' (2): Animal.
	- 'ENTY:body' (3): Organ of body.
	- 'ENTY:color' (4): Color.
	- 'ENTY:cremat' (5): Invention, book and other creative piece.
	- 'ENTY:currency' (6): Currency name.
	- 'ENTY:dismed' (7): Disease and medicine.
	- 'ENTY:event' (8): Event.
	- 'ENTY:food' (9): Food.
	- 'ENTY:instru' (10): Musical instrument.
	- 'ENTY:lang' (11): Language.
	- 'ENTY:letter' (12): Letter like a-z.
	- 'ENTY:other' (13): Other entity.
	- 'ENTY:plant' (14): Plant.
	- 'ENTY:product' (15): Product.
	- 'ENTY:religion' (16): Religion.
	- 'ENTY:sport' (17): Sport.
	- 'ENTY:substance' (18): Element and substance.
	- 'ENTY:symbol' (19): Symbols and sign.
	- 'ENTY:techmeth' (20): Techniques and method.
	- 'ENTY:termeq' (21): Equivalent term.
	- 'ENTY:veh' (22): Vehicle.
	- 'ENTY:word' (23): Word with a special property.
	- DESCRIPTION:
	- 'DESC:def' (24): Definition of something.
	- 'DESC:desc' (25): Description of something.
	- 'DESC:manner' (26): Manner of an action.
	- 'DESC:reason' (27): Reason.
	- HUMAN:
	- 'HUM:gr' (28): Group or organization of persons
	- 'HUM:ind' (29): Individual.
	- 'HUM:title' (30): Title of a person.
	- 'HUM:desc' (31): Description of a person.
	- LOCATION:
	- 'LOC:city' (32): City.
	- 'LOC:country' (33): Country.
	- 'LOC:mount' (34): Mountain.
	- 'LOC:other' (35): Other location.
	- 'LOC:state' (36): State.
	- NUMERIC:
	- 'NUM:code' (37): Postcode or other code.
	- 'NUM:count' (38): Number of something.
	- 'NUM:date' (39): Date.
	- 'NUM:dist' (40): Distance, linear measure.
	- 'NUM:money' (41): Price.
	- 'NUM:ord' (42): Order, rank.
	- 'NUM:other' (43): Other number.
	- 'NUM:period' (44): Lasting time of something
	- 'NUM:perc' (45): Percent, fraction.
	- 'NUM:speed' (46): Speed.
	- 'NUM:temp' (47): Temperature.
	- 'NUM:volsize' (48): Size, area and volume.
	- 'NUM:weight' (49): Weight.


	### Data Splits

	\| name \| train \| test \|
	\|---------\|------:\|-----:\|
	\| default \| 5452 \| 500 \|

	## 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

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

	### Citation Information

	```
	@inproceedings{li-roth-2002-learning,
	title = "Learning Question Classifiers",
	author = "Li, Xin and
	Roth, Dan",
	booktitle = "{COLING} 2002: The 19th International Conference on Computational Linguistics",
	year = "2002",
	url = "https://www.aclweb.org/anthology/C02-1150",
	}
	@inproceedings{hovy-etal-2001-toward,
	title = "Toward Semantics-Based Answer Pinpointing",
	author = "Hovy, Eduard and
	Gerber, Laurie and
	Hermjakob, Ulf and
	Lin, Chin-Yew and
	Ravichandran, Deepak",
	booktitle = "Proceedings of the First International Conference on Human Language Technology Research",
	year = "2001",
	url = "https://www.aclweb.org/anthology/H01-1069",
	}
	```


	### Contributions

	Thanks to [@lhoestq](https://github.com/lhoestq), [@thomwolf](https://github.com/thomwolf) for adding this dataset.