Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
intent-classification
Languages:
English
Size:
10K - 100K
License:
Added dataset information in clinic oos dataset card (#4751)
Browse files* Added Dataset information in Clinic oos card
* Added Field and Instance Information
* Added Label List in Data Fields
* Updated Table Caption
* Update datasets/clinc_oos/README.md
* Update README.md
Co-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com>
Commit from https://github.com/huggingface/datasets/commit/f9713d2e23813142a02f1b0e965095f528785cff
README.md
CHANGED
@@ -21,7 +21,7 @@ paperswithcode_id: clinc150
|
|
21 |
pretty_name: CLINC150
|
22 |
---
|
23 |
|
24 |
-
# Dataset Card for
|
25 |
|
26 |
## Table of Contents
|
27 |
- [Dataset Description](#dataset-description)
|
@@ -52,34 +52,210 @@ pretty_name: CLINC150
|
|
52 |
- **Homepage:** [Github](https://github.com/clinc/oos-eval/)
|
53 |
- **Repository:** [Github](https://github.com/clinc/oos-eval/)
|
54 |
- **Paper:** [Aclweb](https://www.aclweb.org/anthology/D19-1131)
|
55 |
-
- **Leaderboard:**
|
56 |
- **Point of Contact:**
|
57 |
|
58 |
### Dataset Summary
|
59 |
|
60 |
-
|
61 |
|
62 |
### Supported Tasks and Leaderboards
|
63 |
|
64 |
-
|
65 |
|
66 |
### Languages
|
67 |
|
68 |
-
|
69 |
|
70 |
## Dataset Structure
|
71 |
|
72 |
### Data Instances
|
73 |
|
74 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
75 |
|
76 |
### Data Fields
|
77 |
|
78 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
79 |
|
80 |
### Data Splits
|
81 |
|
82 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
83 |
|
84 |
## Dataset Creation
|
85 |
|
@@ -136,8 +312,25 @@ pretty_name: CLINC150
|
|
136 |
[More Information Needed]
|
137 |
|
138 |
### Citation Information
|
139 |
-
|
140 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
141 |
### Contributions
|
142 |
|
143 |
Thanks to [@sumanthd17](https://github.com/sumanthd17) for adding this dataset.
|
|
|
21 |
pretty_name: CLINC150
|
22 |
---
|
23 |
|
24 |
+
# Dataset Card for CLINC150
|
25 |
|
26 |
## Table of Contents
|
27 |
- [Dataset Description](#dataset-description)
|
|
|
52 |
- **Homepage:** [Github](https://github.com/clinc/oos-eval/)
|
53 |
- **Repository:** [Github](https://github.com/clinc/oos-eval/)
|
54 |
- **Paper:** [Aclweb](https://www.aclweb.org/anthology/D19-1131)
|
55 |
+
- **Leaderboard:** [PapersWithCode](https://paperswithcode.com/sota/text-classification-on-clinc-oos)
|
56 |
- **Point of Contact:**
|
57 |
|
58 |
### Dataset Summary
|
59 |
|
60 |
+
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.
|
61 |
|
62 |
### Supported Tasks and Leaderboards
|
63 |
|
64 |
+
- `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).
|
65 |
|
66 |
### Languages
|
67 |
|
68 |
+
English
|
69 |
|
70 |
## Dataset Structure
|
71 |
|
72 |
### Data Instances
|
73 |
|
74 |
+
A sample from the training set is provided below:
|
75 |
+
```
|
76 |
+
{
|
77 |
+
'text' : 'can you walk me through setting up direct deposits to my bank of internet savings account',
|
78 |
+
'label' : 108
|
79 |
+
}
|
80 |
+
```
|
81 |
|
82 |
### Data Fields
|
83 |
|
84 |
+
- text : Textual data
|
85 |
+
- label : 150 intent classes over 10 domains, the dataset contains one label for 'out-of-scope' intent.
|
86 |
+
|
87 |
+
The Label Id to Label Name map is mentioned in the table below:
|
88 |
+
|
89 |
+
| **Label Id** | **Label name** |
|
90 |
+
|--- |--- |
|
91 |
+
| 0 | restaurant_reviews |
|
92 |
+
| 1 | nutrition_info |
|
93 |
+
| 2 | account_blocked |
|
94 |
+
| 3 | oil_change_how |
|
95 |
+
| 4 | time |
|
96 |
+
| 5 | weather |
|
97 |
+
| 6 | redeem_rewards |
|
98 |
+
| 7 | interest_rate |
|
99 |
+
| 8 | gas_type |
|
100 |
+
| 9 | accept_reservations |
|
101 |
+
| 10 | smart_home |
|
102 |
+
| 11 | user_name |
|
103 |
+
| 12 | report_lost_card |
|
104 |
+
| 13 | repeat |
|
105 |
+
| 14 | whisper_mode |
|
106 |
+
| 15 | what_are_your_hobbies |
|
107 |
+
| 16 | order |
|
108 |
+
| 17 | jump_start |
|
109 |
+
| 18 | schedule_meeting |
|
110 |
+
| 19 | meeting_schedule |
|
111 |
+
| 20 | freeze_account |
|
112 |
+
| 21 | what_song |
|
113 |
+
| 22 | meaning_of_life |
|
114 |
+
| 23 | restaurant_reservation |
|
115 |
+
| 24 | traffic |
|
116 |
+
| 25 | make_call |
|
117 |
+
| 26 | text |
|
118 |
+
| 27 | bill_balance |
|
119 |
+
| 28 | improve_credit_score |
|
120 |
+
| 29 | change_language |
|
121 |
+
| 30 | no |
|
122 |
+
| 31 | measurement_conversion |
|
123 |
+
| 32 | timer |
|
124 |
+
| 33 | flip_coin |
|
125 |
+
| 34 | do_you_have_pets |
|
126 |
+
| 35 | balance |
|
127 |
+
| 36 | tell_joke |
|
128 |
+
| 37 | last_maintenance |
|
129 |
+
| 38 | exchange_rate |
|
130 |
+
| 39 | uber |
|
131 |
+
| 40 | car_rental |
|
132 |
+
| 41 | credit_limit |
|
133 |
+
| 42 | oos |
|
134 |
+
| 43 | shopping_list |
|
135 |
+
| 44 | expiration_date |
|
136 |
+
| 45 | routing |
|
137 |
+
| 46 | meal_suggestion |
|
138 |
+
| 47 | tire_change |
|
139 |
+
| 48 | todo_list |
|
140 |
+
| 49 | card_declined |
|
141 |
+
| 50 | rewards_balance |
|
142 |
+
| 51 | change_accent |
|
143 |
+
| 52 | vaccines |
|
144 |
+
| 53 | reminder_update |
|
145 |
+
| 54 | food_last |
|
146 |
+
| 55 | change_ai_name |
|
147 |
+
| 56 | bill_due |
|
148 |
+
| 57 | who_do_you_work_for |
|
149 |
+
| 58 | share_location |
|
150 |
+
| 59 | international_visa |
|
151 |
+
| 60 | calendar |
|
152 |
+
| 61 | translate |
|
153 |
+
| 62 | carry_on |
|
154 |
+
| 63 | book_flight |
|
155 |
+
| 64 | insurance_change |
|
156 |
+
| 65 | todo_list_update |
|
157 |
+
| 66 | timezone |
|
158 |
+
| 67 | cancel_reservation |
|
159 |
+
| 68 | transactions |
|
160 |
+
| 69 | credit_score |
|
161 |
+
| 70 | report_fraud |
|
162 |
+
| 71 | spending_history |
|
163 |
+
| 72 | directions |
|
164 |
+
| 73 | spelling |
|
165 |
+
| 74 | insurance |
|
166 |
+
| 75 | what_is_your_name |
|
167 |
+
| 76 | reminder |
|
168 |
+
| 77 | where_are_you_from |
|
169 |
+
| 78 | distance |
|
170 |
+
| 79 | payday |
|
171 |
+
| 80 | flight_status |
|
172 |
+
| 81 | find_phone |
|
173 |
+
| 82 | greeting |
|
174 |
+
| 83 | alarm |
|
175 |
+
| 84 | order_status |
|
176 |
+
| 85 | confirm_reservation |
|
177 |
+
| 86 | cook_time |
|
178 |
+
| 87 | damaged_card |
|
179 |
+
| 88 | reset_settings |
|
180 |
+
| 89 | pin_change |
|
181 |
+
| 90 | replacement_card_duration |
|
182 |
+
| 91 | new_card |
|
183 |
+
| 92 | roll_dice |
|
184 |
+
| 93 | income |
|
185 |
+
| 94 | taxes |
|
186 |
+
| 95 | date |
|
187 |
+
| 96 | who_made_you |
|
188 |
+
| 97 | pto_request |
|
189 |
+
| 98 | tire_pressure |
|
190 |
+
| 99 | how_old_are_you |
|
191 |
+
| 100 | rollover_401k |
|
192 |
+
| 101 | pto_request_status |
|
193 |
+
| 102 | how_busy |
|
194 |
+
| 103 | application_status |
|
195 |
+
| 104 | recipe |
|
196 |
+
| 105 | calendar_update |
|
197 |
+
| 106 | play_music |
|
198 |
+
| 107 | yes |
|
199 |
+
| 108 | direct_deposit |
|
200 |
+
| 109 | credit_limit_change |
|
201 |
+
| 110 | gas |
|
202 |
+
| 111 | pay_bill |
|
203 |
+
| 112 | ingredients_list |
|
204 |
+
| 113 | lost_luggage |
|
205 |
+
| 114 | goodbye |
|
206 |
+
| 115 | what_can_i_ask_you |
|
207 |
+
| 116 | book_hotel |
|
208 |
+
| 117 | are_you_a_bot |
|
209 |
+
| 118 | next_song |
|
210 |
+
| 119 | change_speed |
|
211 |
+
| 120 | plug_type |
|
212 |
+
| 121 | maybe |
|
213 |
+
| 122 | w2 |
|
214 |
+
| 123 | oil_change_when |
|
215 |
+
| 124 | thank_you |
|
216 |
+
| 125 | shopping_list_update |
|
217 |
+
| 126 | pto_balance |
|
218 |
+
| 127 | order_checks |
|
219 |
+
| 128 | travel_alert |
|
220 |
+
| 129 | fun_fact |
|
221 |
+
| 130 | sync_device |
|
222 |
+
| 131 | schedule_maintenance |
|
223 |
+
| 132 | apr |
|
224 |
+
| 133 | transfer |
|
225 |
+
| 134 | ingredient_substitution |
|
226 |
+
| 135 | calories |
|
227 |
+
| 136 | current_location |
|
228 |
+
| 137 | international_fees |
|
229 |
+
| 138 | calculator |
|
230 |
+
| 139 | definition |
|
231 |
+
| 140 | next_holiday |
|
232 |
+
| 141 | update_playlist |
|
233 |
+
| 142 | mpg |
|
234 |
+
| 143 | min_payment |
|
235 |
+
| 144 | change_user_name |
|
236 |
+
| 145 | restaurant_suggestion |
|
237 |
+
| 146 | travel_notification |
|
238 |
+
| 147 | cancel |
|
239 |
+
| 148 | pto_used |
|
240 |
+
| 149 | travel_suggestion |
|
241 |
+
| 150 | change_volume |
|
242 |
|
243 |
### Data Splits
|
244 |
|
245 |
+
The dataset comes in different subsets:
|
246 |
+
|
247 |
+
- `small` : Small, in which there are only 50 training queries per each in-scope intent
|
248 |
+
- `imbalanced` : Imbalanced, in which intents have either 25, 50, 75, or 100 training queries.
|
249 |
+
- `plus`: OOS+, in which there are 250 out-of-scope training examples, rather than 100.
|
250 |
+
|
251 |
+
|
252 |
+
| name |train|validation|test|
|
253 |
+
|----------|----:|---------:|---:|
|
254 |
+
|small|7600| 3100| 5500 |
|
255 |
+
|imbalanced|10625| 3100| 5500|
|
256 |
+
|plus|15250| 3100| 5500|
|
257 |
+
|
258 |
+
|
259 |
|
260 |
## Dataset Creation
|
261 |
|
|
|
312 |
[More Information Needed]
|
313 |
|
314 |
### Citation Information
|
315 |
+
```
|
316 |
+
@inproceedings{larson-etal-2019-evaluation,
|
317 |
+
title = "An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction",
|
318 |
+
author = "Larson, Stefan and
|
319 |
+
Mahendran, Anish and
|
320 |
+
Peper, Joseph J. and
|
321 |
+
Clarke, Christopher and
|
322 |
+
Lee, Andrew and
|
323 |
+
Hill, Parker and
|
324 |
+
Kummerfeld, Jonathan K. and
|
325 |
+
Leach, Kevin and
|
326 |
+
Laurenzano, Michael A. and
|
327 |
+
Tang, Lingjia and
|
328 |
+
Mars, Jason",
|
329 |
+
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)",
|
330 |
+
year = "2019",
|
331 |
+
url = "https://www.aclweb.org/anthology/D19-1131"
|
332 |
+
}
|
333 |
+
```
|
334 |
### Contributions
|
335 |
|
336 |
Thanks to [@sumanthd17](https://github.com/sumanthd17) for adding this dataset.
|