Datasets:

clinc
/

clinc_oos

	---
	annotations_creators:
	- expert-generated
	language_creators:
	- crowdsourced
	language:
	- en
	license:
	- cc-by-3.0
	multilinguality:
	- monolingual
	size_categories:
	- 10K<n<100K
	source_datasets:
	- original
	task_categories:
	- text-classification
	task_ids:
	- intent-classification
	paperswithcode_id: clinc150
	pretty_name: CLINC150
	dataset_info:
	- config_name: small
	features:
	- name: text
	dtype: string
	- name: intent
	dtype:
	class_label:
	names:
	0: restaurant_reviews
	1: nutrition_info
	2: account_blocked
	3: oil_change_how
	4: time
	5: weather
	6: redeem_rewards
	7: interest_rate
	8: gas_type
	9: accept_reservations
	10: smart_home
	11: user_name
	12: report_lost_card
	13: repeat
	14: whisper_mode
	15: what_are_your_hobbies
	16: order
	17: jump_start
	18: schedule_meeting
	19: meeting_schedule
	20: freeze_account
	21: what_song
	22: meaning_of_life
	23: restaurant_reservation
	24: traffic
	25: make_call
	26: text
	27: bill_balance
	28: improve_credit_score
	29: change_language
	30: 'no'
	31: measurement_conversion
	32: timer
	33: flip_coin
	34: do_you_have_pets
	35: balance
	36: tell_joke
	37: last_maintenance
	38: exchange_rate
	39: uber
	40: car_rental
	41: credit_limit
	42: oos
	43: shopping_list
	44: expiration_date
	45: routing
	46: meal_suggestion
	47: tire_change
	48: todo_list
	49: card_declined
	50: rewards_balance
	51: change_accent
	52: vaccines
	53: reminder_update
	54: food_last
	55: change_ai_name
	56: bill_due
	57: who_do_you_work_for
	58: share_location
	59: international_visa
	60: calendar
	61: translate
	62: carry_on
	63: book_flight
	64: insurance_change
	65: todo_list_update
	66: timezone
	67: cancel_reservation
	68: transactions
	69: credit_score
	70: report_fraud
	71: spending_history
	72: directions
	73: spelling
	74: insurance
	75: what_is_your_name
	76: reminder
	77: where_are_you_from
	78: distance
	79: payday
	80: flight_status
	81: find_phone
	82: greeting
	83: alarm
	84: order_status
	85: confirm_reservation
	86: cook_time
	87: damaged_card
	88: reset_settings
	89: pin_change
	90: replacement_card_duration
	91: new_card
	92: roll_dice
	93: income
	94: taxes
	95: date
	96: who_made_you
	97: pto_request
	98: tire_pressure
	99: how_old_are_you
	100: rollover_401k
	101: pto_request_status
	102: how_busy
	103: application_status
	104: recipe
	105: calendar_update
	106: play_music
	107: 'yes'
	108: direct_deposit
	109: credit_limit_change
	110: gas
	111: pay_bill
	112: ingredients_list
	113: lost_luggage
	114: goodbye
	115: what_can_i_ask_you
	116: book_hotel
	117: are_you_a_bot
	118: next_song
	119: change_speed
	120: plug_type
	121: maybe
	122: w2
	123: oil_change_when
	124: thank_you
	125: shopping_list_update
	126: pto_balance
	127: order_checks
	128: travel_alert
	129: fun_fact
	130: sync_device
	131: schedule_maintenance
	132: apr
	133: transfer
	134: ingredient_substitution
	135: calories
	136: current_location
	137: international_fees
	138: calculator
	139: definition
	140: next_holiday
	141: update_playlist
	142: mpg
	143: min_payment
	144: change_user_name
	145: restaurant_suggestion
	146: travel_notification
	147: cancel
	148: pto_used
	149: travel_suggestion
	150: change_volume
	splits:
	- name: train
	num_bytes: 394128
	num_examples: 7600
	- name: validation
	num_bytes: 160302
	num_examples: 3100
	- name: test
	num_bytes: 286970
	num_examples: 5500
	download_size: 1702451
	dataset_size: 841400
	- config_name: imbalanced
	features:
	- name: text
	dtype: string
	- name: intent
	dtype:
	class_label:
	names:
	0: restaurant_reviews
	1: nutrition_info
	2: account_blocked
	3: oil_change_how
	4: time
	5: weather
	6: redeem_rewards
	7: interest_rate
	8: gas_type
	9: accept_reservations
	10: smart_home
	11: user_name
	12: report_lost_card
	13: repeat
	14: whisper_mode
	15: what_are_your_hobbies
	16: order
	17: jump_start
	18: schedule_meeting
	19: meeting_schedule
	20: freeze_account
	21: what_song
	22: meaning_of_life
	23: restaurant_reservation
	24: traffic
	25: make_call
	26: text
	27: bill_balance
	28: improve_credit_score
	29: change_language
	30: 'no'
	31: measurement_conversion
	32: timer
	33: flip_coin
	34: do_you_have_pets
	35: balance
	36: tell_joke
	37: last_maintenance
	38: exchange_rate
	39: uber
	40: car_rental
	41: credit_limit
	42: oos
	43: shopping_list
	44: expiration_date
	45: routing
	46: meal_suggestion
	47: tire_change
	48: todo_list
	49: card_declined
	50: rewards_balance
	51: change_accent
	52: vaccines
	53: reminder_update
	54: food_last
	55: change_ai_name
	56: bill_due
	57: who_do_you_work_for
	58: share_location
	59: international_visa
	60: calendar
	61: translate
	62: carry_on
	63: book_flight
	64: insurance_change
	65: todo_list_update
	66: timezone
	67: cancel_reservation
	68: transactions
	69: credit_score
	70: report_fraud
	71: spending_history
	72: directions
	73: spelling
	74: insurance
	75: what_is_your_name
	76: reminder
	77: where_are_you_from
	78: distance
	79: payday
	80: flight_status
	81: find_phone
	82: greeting
	83: alarm
	84: order_status
	85: confirm_reservation
	86: cook_time
	87: damaged_card
	88: reset_settings
	89: pin_change
	90: replacement_card_duration
	91: new_card
	92: roll_dice
	93: income
	94: taxes
	95: date
	96: who_made_you
	97: pto_request
	98: tire_pressure
	99: how_old_are_you
	100: rollover_401k
	101: pto_request_status
	102: how_busy
	103: application_status
	104: recipe
	105: calendar_update
	106: play_music
	107: 'yes'
	108: direct_deposit
	109: credit_limit_change
	110: gas
	111: pay_bill
	112: ingredients_list
	113: lost_luggage
	114: goodbye
	115: what_can_i_ask_you
	116: book_hotel
	117: are_you_a_bot
	118: next_song
	119: change_speed
	120: plug_type
	121: maybe
	122: w2
	123: oil_change_when
	124: thank_you
	125: shopping_list_update
	126: pto_balance
	127: order_checks
	128: travel_alert
	129: fun_fact
	130: sync_device
	131: schedule_maintenance
	132: apr
	133: transfer
	134: ingredient_substitution
	135: calories
	136: current_location
	137: international_fees
	138: calculator
	139: definition
	140: next_holiday
	141: update_playlist
	142: mpg
	143: min_payment
	144: change_user_name
	145: restaurant_suggestion
	146: travel_notification
	147: cancel
	148: pto_used
	149: travel_suggestion
	150: change_volume
	splits:
	- name: train
	num_bytes: 546909
	num_examples: 10625
	- name: validation
	num_bytes: 160302
	num_examples: 3100
	- name: test
	num_bytes: 286970
	num_examples: 5500
	download_size: 2016773
	dataset_size: 994181
	- config_name: plus
	features:
	- name: text
	dtype: string
	- name: intent
	dtype:
	class_label:
	names:
	0: restaurant_reviews
	1: nutrition_info
	2: account_blocked
	3: oil_change_how
	4: time
	5: weather
	6: redeem_rewards
	7: interest_rate
	8: gas_type
	9: accept_reservations
	10: smart_home
	11: user_name
	12: report_lost_card
	13: repeat
	14: whisper_mode
	15: what_are_your_hobbies
	16: order
	17: jump_start
	18: schedule_meeting
	19: meeting_schedule
	20: freeze_account
	21: what_song
	22: meaning_of_life
	23: restaurant_reservation
	24: traffic
	25: make_call
	26: text
	27: bill_balance
	28: improve_credit_score
	29: change_language
	30: 'no'
	31: measurement_conversion
	32: timer
	33: flip_coin
	34: do_you_have_pets
	35: balance
	36: tell_joke
	37: last_maintenance
	38: exchange_rate
	39: uber
	40: car_rental
	41: credit_limit
	42: oos
	43: shopping_list
	44: expiration_date
	45: routing
	46: meal_suggestion
	47: tire_change
	48: todo_list
	49: card_declined
	50: rewards_balance
	51: change_accent
	52: vaccines
	53: reminder_update
	54: food_last
	55: change_ai_name
	56: bill_due
	57: who_do_you_work_for
	58: share_location
	59: international_visa
	60: calendar
	61: translate
	62: carry_on
	63: book_flight
	64: insurance_change
	65: todo_list_update
	66: timezone
	67: cancel_reservation
	68: transactions
	69: credit_score
	70: report_fraud
	71: spending_history
	72: directions
	73: spelling
	74: insurance
	75: what_is_your_name
	76: reminder
	77: where_are_you_from
	78: distance
	79: payday
	80: flight_status
	81: find_phone
	82: greeting
	83: alarm
	84: order_status
	85: confirm_reservation
	86: cook_time
	87: damaged_card
	88: reset_settings
	89: pin_change
	90: replacement_card_duration
	91: new_card
	92: roll_dice
	93: income
	94: taxes
	95: date
	96: who_made_you
	97: pto_request
	98: tire_pressure
	99: how_old_are_you
	100: rollover_401k
	101: pto_request_status
	102: how_busy
	103: application_status
	104: recipe
	105: calendar_update
	106: play_music
	107: 'yes'
	108: direct_deposit
	109: credit_limit_change
	110: gas
	111: pay_bill
	112: ingredients_list
	113: lost_luggage
	114: goodbye
	115: what_can_i_ask_you
	116: book_hotel
	117: are_you_a_bot
	118: next_song
	119: change_speed
	120: plug_type
	121: maybe
	122: w2
	123: oil_change_when
	124: thank_you
	125: shopping_list_update
	126: pto_balance
	127: order_checks
	128: travel_alert
	129: fun_fact
	130: sync_device
	131: schedule_maintenance
	132: apr
	133: transfer
	134: ingredient_substitution
	135: calories
	136: current_location
	137: international_fees
	138: calculator
	139: definition
	140: next_holiday
	141: update_playlist
	142: mpg
	143: min_payment
	144: change_user_name
	145: restaurant_suggestion
	146: travel_notification
	147: cancel
	148: pto_used
	149: travel_suggestion
	150: change_volume
	splits:
	- name: train
	num_bytes: 791255
	num_examples: 15250
	- name: validation
	num_bytes: 160302
	num_examples: 3100
	- name: test
	num_bytes: 286970
	num_examples: 5500
	download_size: 2509789
	dataset_size: 1238527
	---

	# Dataset Card for CLINC150

	## 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: [Github](https://github.com/clinc/oos-eval/)
	- Repository: [Github](https://github.com/clinc/oos-eval/)
	- Paper: [Aclweb](https://www.aclweb.org/anthology/D19-1131)
	- Leaderboard: [PapersWithCode](https://paperswithcode.com/sota/text-classification-on-clinc-oos)
	- Point of Contact:

	### Dataset Summary

	Task-oriented dialog systems need to know when a query falls outside their range of supported intents, but current text classification corpora only define label sets that cover every example. We introduce a new dataset that includes queries that are out-of-scope (OOS), i.e., queries that do not fall into any of the system's supported intents. This poses a new challenge because models cannot assume that every query at inference time belongs to a system-supported intent class. Our dataset also covers 150 intent classes over 10 domains, capturing the breadth that a production task-oriented agent must handle. It offers a way of more rigorously and realistically benchmarking text classification in task-driven dialog systems.

	### Supported Tasks and Leaderboards

	- `intent-classification`: This dataset is for evaluating the performance of intent classification systems in the presence of "out-of-scope" queries, i.e., queries that do not fall into any of the system-supported intent classes. The dataset includes both in-scope and out-of-scope data. [here](https://paperswithcode.com/sota/text-classification-on-clinc-oos).

	### Languages

	English

	## Dataset Structure

	### Data Instances

	A sample from the training set is provided below:
	```
	{
	'text' : 'can you walk me through setting up direct deposits to my bank of internet savings account',
	'label' : 108
	}
	```

	### Data Fields

	- text : Textual data
	- label : 150 intent classes over 10 domains, the dataset contains one label for 'out-of-scope' intent.

	The Label Id to Label Name map is mentioned in the table below:

	\| Label Id \| Label name \|
	\|--- \|--- \|
	\| 0 \| restaurant_reviews \|
	\| 1 \| nutrition_info \|
	\| 2 \| account_blocked \|
	\| 3 \| oil_change_how \|
	\| 4 \| time \|
	\| 5 \| weather \|
	\| 6 \| redeem_rewards \|
	\| 7 \| interest_rate \|
	\| 8 \| gas_type \|
	\| 9 \| accept_reservations \|
	\| 10 \| smart_home \|
	\| 11 \| user_name \|
	\| 12 \| report_lost_card \|
	\| 13 \| repeat \|
	\| 14 \| whisper_mode \|
	\| 15 \| what_are_your_hobbies \|
	\| 16 \| order \|
	\| 17 \| jump_start \|
	\| 18 \| schedule_meeting \|
	\| 19 \| meeting_schedule \|
	\| 20 \| freeze_account \|
	\| 21 \| what_song \|
	\| 22 \| meaning_of_life \|
	\| 23 \| restaurant_reservation \|
	\| 24 \| traffic \|
	\| 25 \| make_call \|
	\| 26 \| text \|
	\| 27 \| bill_balance \|
	\| 28 \| improve_credit_score \|
	\| 29 \| change_language \|
	\| 30 \| no \|
	\| 31 \| measurement_conversion \|
	\| 32 \| timer \|
	\| 33 \| flip_coin \|
	\| 34 \| do_you_have_pets \|
	\| 35 \| balance \|
	\| 36 \| tell_joke \|
	\| 37 \| last_maintenance \|
	\| 38 \| exchange_rate \|
	\| 39 \| uber \|
	\| 40 \| car_rental \|
	\| 41 \| credit_limit \|
	\| 42 \| oos \|
	\| 43 \| shopping_list \|
	\| 44 \| expiration_date \|
	\| 45 \| routing \|
	\| 46 \| meal_suggestion \|
	\| 47 \| tire_change \|
	\| 48 \| todo_list \|
	\| 49 \| card_declined \|
	\| 50 \| rewards_balance \|
	\| 51 \| change_accent \|
	\| 52 \| vaccines \|
	\| 53 \| reminder_update \|
	\| 54 \| food_last \|
	\| 55 \| change_ai_name \|
	\| 56 \| bill_due \|
	\| 57 \| who_do_you_work_for \|
	\| 58 \| share_location \|
	\| 59 \| international_visa \|
	\| 60 \| calendar \|
	\| 61 \| translate \|
	\| 62 \| carry_on \|
	\| 63 \| book_flight \|
	\| 64 \| insurance_change \|
	\| 65 \| todo_list_update \|
	\| 66 \| timezone \|
	\| 67 \| cancel_reservation \|
	\| 68 \| transactions \|
	\| 69 \| credit_score \|
	\| 70 \| report_fraud \|
	\| 71 \| spending_history \|
	\| 72 \| directions \|
	\| 73 \| spelling \|
	\| 74 \| insurance \|
	\| 75 \| what_is_your_name \|
	\| 76 \| reminder \|
	\| 77 \| where_are_you_from \|
	\| 78 \| distance \|
	\| 79 \| payday \|
	\| 80 \| flight_status \|
	\| 81 \| find_phone \|
	\| 82 \| greeting \|
	\| 83 \| alarm \|
	\| 84 \| order_status \|
	\| 85 \| confirm_reservation \|
	\| 86 \| cook_time \|
	\| 87 \| damaged_card \|
	\| 88 \| reset_settings \|
	\| 89 \| pin_change \|
	\| 90 \| replacement_card_duration \|
	\| 91 \| new_card \|
	\| 92 \| roll_dice \|
	\| 93 \| income \|
	\| 94 \| taxes \|
	\| 95 \| date \|
	\| 96 \| who_made_you \|
	\| 97 \| pto_request \|
	\| 98 \| tire_pressure \|
	\| 99 \| how_old_are_you \|
	\| 100 \| rollover_401k \|
	\| 101 \| pto_request_status \|
	\| 102 \| how_busy \|
	\| 103 \| application_status \|
	\| 104 \| recipe \|
	\| 105 \| calendar_update \|
	\| 106 \| play_music \|
	\| 107 \| yes \|
	\| 108 \| direct_deposit \|
	\| 109 \| credit_limit_change \|
	\| 110 \| gas \|
	\| 111 \| pay_bill \|
	\| 112 \| ingredients_list \|
	\| 113 \| lost_luggage \|
	\| 114 \| goodbye \|
	\| 115 \| what_can_i_ask_you \|
	\| 116 \| book_hotel \|
	\| 117 \| are_you_a_bot \|
	\| 118 \| next_song \|
	\| 119 \| change_speed \|
	\| 120 \| plug_type \|
	\| 121 \| maybe \|
	\| 122 \| w2 \|
	\| 123 \| oil_change_when \|
	\| 124 \| thank_you \|
	\| 125 \| shopping_list_update \|
	\| 126 \| pto_balance \|
	\| 127 \| order_checks \|
	\| 128 \| travel_alert \|
	\| 129 \| fun_fact \|
	\| 130 \| sync_device \|
	\| 131 \| schedule_maintenance \|
	\| 132 \| apr \|
	\| 133 \| transfer \|
	\| 134 \| ingredient_substitution \|
	\| 135 \| calories \|
	\| 136 \| current_location \|
	\| 137 \| international_fees \|
	\| 138 \| calculator \|
	\| 139 \| definition \|
	\| 140 \| next_holiday \|
	\| 141 \| update_playlist \|
	\| 142 \| mpg \|
	\| 143 \| min_payment \|
	\| 144 \| change_user_name \|
	\| 145 \| restaurant_suggestion \|
	\| 146 \| travel_notification \|
	\| 147 \| cancel \|
	\| 148 \| pto_used \|
	\| 149 \| travel_suggestion \|
	\| 150 \| change_volume \|

	### Data Splits

	The dataset comes in different subsets:

	- `small` : Small, in which there are only 50 training queries per each in-scope intent
	- `imbalanced` : Imbalanced, in which intents have either 25, 50, 75, or 100 training queries.
	- `plus`: OOS+, in which there are 250 out-of-scope training examples, rather than 100.


	\| name \|train\|validation\|test\|
	\|----------\|----:\|---------:\|---:\|
	\|small\|7600\| 3100\| 5500 \|
	\|imbalanced\|10625\| 3100\| 5500\|
	\|plus\|15250\| 3100\| 5500\|



	## Dataset Creation

	### Curation Rationale

	[More Information Needed]

	### Source Data

	#### Initial Data Collection and Normalization

	[More Information Needed]

	#### Who are the source language producers?

	[More Information Needed]

	### Annotations

	#### Annotation process

	[More Information Needed]

	#### Who are the annotators?

	[More Information Needed]

	### Personal and Sensitive Information

	[More Information Needed]

	## Considerations for Using the Data

	### Social Impact of Dataset

	[More Information Needed]

	### Discussion of Biases

	[More Information Needed]

	### Other Known Limitations

	[More Information Needed]

	## Additional Information

	### Dataset Curators

	[More Information Needed]

	### Licensing Information

	[More Information Needed]

	### Citation Information
	```
	@inproceedings{larson-etal-2019-evaluation,
	title = "An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction",
	author = "Larson, Stefan and
	Mahendran, Anish and
	Peper, Joseph J. and
	Clarke, Christopher and
	Lee, Andrew and
	Hill, Parker and
	Kummerfeld, Jonathan K. and
	Leach, Kevin and
	Laurenzano, Michael A. and
	Tang, Lingjia and
	Mars, Jason",
	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)",
	year = "2019",
	url = "https://www.aclweb.org/anthology/D19-1131"
	}
	```
	### Contributions

	Thanks to [@sumanthd17](https://github.com/sumanthd17) for adding this dataset.