Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
intent-classification
Languages:
English
Size:
10K - 100K
License:
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: 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: 546901 | |
num_examples: 10625 | |
- name: validation | |
num_bytes: 160298 | |
num_examples: 3100 | |
- name: test | |
num_bytes: 286966 | |
num_examples: 5500 | |
download_size: 441918 | |
dataset_size: 994165 | |
- 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: 791247 | |
num_examples: 15250 | |
- name: validation | |
num_bytes: 160298 | |
num_examples: 3100 | |
- name: test | |
num_bytes: 286966 | |
num_examples: 5500 | |
download_size: 525729 | |
dataset_size: 1238511 | |
- 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: 394124 | |
num_examples: 7600 | |
- name: validation | |
num_bytes: 160298 | |
num_examples: 3100 | |
- name: test | |
num_bytes: 286966 | |
num_examples: 5500 | |
download_size: 385185 | |
dataset_size: 841388 | |
configs: | |
- config_name: imbalanced | |
data_files: | |
- split: train | |
path: imbalanced/train-* | |
- split: validation | |
path: imbalanced/validation-* | |
- split: test | |
path: imbalanced/test-* | |
- config_name: plus | |
data_files: | |
- split: train | |
path: plus/train-* | |
- split: validation | |
path: plus/validation-* | |
- split: test | |
path: plus/test-* | |
- config_name: small | |
data_files: | |
- split: train | |
path: small/train-* | |
- split: validation | |
path: small/validation-* | |
- split: test | |
path: small/test-* | |
# 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. |