├── README.rst
├── LICENSE
└── BETOLD_description.md
/README.rst:
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1 | ================================================================================
2 | Data of the paper "BETOLD: A Task-Oriented Dialog Dataset for Dialog Breakdown"
3 | ================================================================================
4 |
5 | .. image:: https://img.shields.io/github/license/telepathylabsai/BETOLD_dataset
6 | :alt: GitHub
7 |
8 | **BETOLD** (Breakdown Expectation for Task-Oriented Long Dialogs) is a
9 | task-oriented dialog dataset, derived from real conversations between system
10 | and user in order to fulfill the task of booking an appointment.
11 | The aim of the dataset is to predict **LUFHs**, i.e. **user-initiated (U) forward calls (F)
12 | and hang-ups (H) that happen in a late (L) point of the conversation**.
13 | This dataset is characterized by NLG and NLU intents and entities.
14 | It does not provide textual utterances.
15 |
16 | This work has been accepted at the COLING 2022's
17 | workshop "When creative AI meets conversational AI". `Click here to read the paper `_!
18 |
19 |
20 | ******************
21 | Dataset
22 | ******************
23 |
24 | Dataset Features
25 | ==================
26 |
27 | All dialogs include:
28 |
29 | * LUHF: binary label 'luhf' or 'not_luhf'.
30 | * utterances_annotations: contains all NLU and NLG intents and entities.
31 |
32 | * caller_name: indicates if it is a NLU (i.e a user input) or NLG (i.e a system input).
33 | * intent: the purpose which the speaker wants to achieve.
34 | * entities: slots extracted from NLU and NLG giving context to the conversation.
35 |
36 |
37 | Structure
38 | ==================
39 |
40 | The dataset is structured in the following way:
41 |
42 | .. code-block:: bash
43 |
44 | [
45 | {
46 | "LUHF": "luhf", # binary label 'luhf' or 'not_luhf'
47 | "utterances_annotations": [ # list of interactions between system and human
48 | {
49 | "caller_name": "nlg",
50 | "intent": "intro_assistant_1",
51 | "entities": [
52 | {
53 | "entity": "recording_warning"
54 | }
55 | ]
56 | },
57 | {
58 | "caller_name": "nlg",
59 | "intent": "intro_assistant_2",
60 | "entities": [
61 | ]
62 | },
63 | {
64 | "caller_name": "nlu",
65 | "intent": "schedule",
66 | "entities": [
67 | ]
68 | },
69 | # ...
70 | ]
71 | },
72 | # ...
73 | ]
74 |
75 |
76 | See the file `BETOLD_description.md `_
77 | and the `paper `_ for more details on the creation of the dataset and on the features.
78 |
79 |
80 |
81 | ******************
82 | Models
83 | ******************
84 | See this repository for the models' implementation: https://github.com/telepathylabsai/dialog_breakdown_detection
85 |
86 |
87 | ******************
88 | Team
89 | ******************
90 |
91 | - Silvia Terragni
92 | - Bruna Guedes
93 | - Andre Manso
94 | - Modestas Filipavicius
95 | - Nghia Khau
96 | - Roland Mathis
97 |
98 |
99 | ***********************
100 | How to cite this work
101 | ***********************
102 | This work has been accepted at the COLING 2022's workshop `When creative AI meets conversational AI `_.
103 | If you decide to use this resource, please cite:
104 |
105 | ::
106 |
107 | @inproceedings{terragni2022_betold,
108 | title = "{BETOLD}: A Task-Oriented Dialog Dataset for Breakdown Detection",
109 | author = "Terragni, Silvia and
110 | Guedes, Bruna and
111 | Manso, Andre and
112 | Filipavicius, Modestas and
113 | Khau, Nghia and
114 | Mathis, Roland",
115 | booktitle = "Proceedings of the Second Workshop on When Creative AI Meets Conversational AI",
116 | month = oct,
117 | year = "2022",
118 | address = "Gyeongju, Republic of Korea",
119 | publisher = "Association for Computational Linguistics",
120 | url = "https://aclanthology.org/2022.cai-1.4",
121 | pages = "23--34",
122 | }
123 |
124 |
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/BETOLD_description.md:
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1 | # Dataset
2 |
3 | ### Overview
4 | Breakdown Expectation for Task-Oriented Long Dialogs (BETOLD) is a
5 | Privacy-Preserving dataset, derived from real conversations between system
6 | and user in order to fulfill the task of booking an appointment.
7 | This dataset was anonymized, by removing text or any natural language derived
8 | from utterances.
9 |
10 | This dataset is made of long dialogs of at least 8 turns, in which each turn
11 | is defined by the change in speaker. The aim of the dataset is to predict
12 | user-initiated (U) forward calls (F) and hang-ups (H) that happen in a late
13 | (L) point of the conversation. Therefore all conversations are labeled either
14 | as LUHF or non-LUHF.
15 |
16 | ### Numbers
17 | This dataset contains 13,524 conversations, with a ratio of successful
18 | calls/LUHFs of 2:1.
19 | The resulting dataset contains 4,508 LUHFs and 9,016 non-LUHFs.
20 |
21 | - min number of turns per dialog: 8
22 | - mean number of turns per dialog: 10.42
23 | - median number of turns per dialog: 10.0
24 | - max number of turns per dialog: 34
25 |
26 | ### Dataset Features
27 | All dialogs include:
28 | - LUHF: binary label 'luhf' or 'not_luhf'.
29 | - utterances_annotations: contains all NLU and NLG intents and entities.
30 | - caller_name: indicates if it is a NLU (i.e a user input) or NLG (i.e a system input).
31 | - intent: the purpose which the speaker wants to achieve.
32 | - entities: slots extracted from NLU and NLG giving context to the conversation.
33 |
34 | ### Structure
35 | The dataset is structured in the following way:
36 |
37 | ```bash
38 | [
39 | {
40 | "LUHF": "luhf", # binary label 'luhf' or 'not_luhf'
41 | "utterances_annotations": [ # list of interactions between system and human
42 | {
43 | "caller_name": "nlg",
44 | "intent": "intro_assistant_1",
45 | "entities": [
46 | {
47 | "entity": "recording_warning"
48 | }
49 | ]
50 | },
51 | {
52 | "caller_name": "nlg",
53 | "intent": "intro_assistant_2",
54 | "entities": [
55 | ]
56 | },
57 | {
58 | "caller_name": "nlu",
59 | "intent": "schedule",
60 | "entities": [
61 | ]
62 | },
63 | # ...
64 | ]
65 | },
66 | # ...
67 | ]
68 | ```
69 |
70 | ### List of possible entities
71 |
72 | | Type | Entity | Description
73 | | :--- | :--- | :---
74 | |NLG | alternative_date_proposal | date of alternative time for appointment |
75 | |NLG | ask_means_of_transportation | means of transportation proposed |
76 | |NLG | ask_to_schedule | confirmation of next steps of scheduling appointment |
77 | |NLG | available_slot_to_schedule | time of slot available for scheduling appointment |
78 | |NLG | closing_hours | closing hours of given store |
79 | |NLG | date_proposal | date proposed |
80 | |NLG | device_make | brand of cellphone |
81 | |NLG | device_model | model of cellphone |
82 | |NLG | device_year | year of fabrication of cellphone |
83 | |NLG | exception_days | days with different working hours |
84 | |NLG | location_store | address of a given store |
85 | |NLG | mention_means_of_transportation | means of transportation chosen |
86 | |NLG | no_slots_available | no options of slots for scheduling appointment are available |
87 | |NLG | opening_days | opening days of week |
88 | |NLG | opening_hours | opening hours |
89 | |NLG | recording_warning | warning this message might be recorded |
90 | |NLG | schedule_time | specific time indication for scheduling appointment |
91 | |NLG | services_closing_hours | closing hours of given service |
92 | |NLG | transportation_type_selection | transportation type selected |
93 | |NLG | unavailable_transportation_type | transportation type is not supported |
94 | |NLG | user_phone_suffix | suffix of user's phone number |
95 | |NLG | user_request_start_time | starting time for scheduling appointment |
96 | |NLU | brand_device | specific brand of cellphone |
97 | |NLU | client_name | name of user |
98 | |NLU | language | language preference specification |
99 | |NLU | model_device | speficific model of cellphone |
100 | |NLU | numeric | numbers, that might be for instance the percentage of battery health |
101 | |NLU | phone_number | phone number |
102 | |NLU | sector | specific department of company |
103 | |NLU | time_indication | specific time indication |
104 | |NLU | time_range_indication | range of time preferred |
105 | |NLU | transportation_type | type of transportation of cellphone, can be pick up, dropoff or waiting for service |
106 | |NLU | type_of_repair | type of repair service required |
107 | |NLU | year | year |
108 |
109 |
110 |
111 | ### List of possible intents
112 |
113 | | Type | Intent | Description
114 | | :--- | :--- | :---
115 | |NLG | ask_additional_service | ask if other services were required |
116 | |NLG | ask_corrected_date | confirm if date should be corrected |
117 | |NLG | ask_desired_service | ask to specify service of cellphone |
118 | |NLG | ask_device_brand | ask to specify brand of cellphone |
119 | |NLG | ask_device_brand_model | ask to specify brand and model of cellphone |
120 | |NLG | ask_device_brand_model_year | ask to specify brand, model and year of cellphone |
121 | |NLG | ask_device_model | ask to specify model of cellphone |
122 | |NLG | ask_device_year | ask to specify year of cellphone |
123 | |NLG | ask_device_year_brand | ask to specify year and brand of cellphone |
124 | |NLG | ask_device_year_model | ask to specify year and model of cellphone |
125 | |NLG | ask_first_name | ask user's first name |
126 | |NLG | ask_for_battery_health | ask battery health from cellphone |
127 | |NLG | ask_if_current_client | ask if user is a current client |
128 | |NLG | ask_last_name | ask user's last name |
129 | |NLG | ask_phone_number | ask user's phone number |
130 | |NLG | ask_time_preference | ask user if there is a time preference |
131 | |NLG | asked_date_too_far | tell user date chosen is too far in the future |
132 | |NLG | confirm_cancel_schedule_new | confirm cancelation of appointment and ask new date |
133 | |NLG | confirm_canceled_appointment | confirm appointment was successfully canceled |
134 | |NLG | confirm_change_schedule | confirm change in date of appointment |
135 | |NLG | confirm_date_scheduled | confirm date of appointment |
136 | |NLG | confirm_phone_number | confirm user's phone number |
137 | |NLG | date_schedule_no_longer_exists | date proposed is no longer available |
138 | |NLG | did_not_understand | system does not understand user |
139 | |NLG | disambiguate_user_profile | disambiguate profile in case of multiple profiles linked to one phone number |
140 | |NLG | fail_retrieve_user_info | unable to find user's profile |
141 | |NLG | failed_schedule_warning | system failure to schedule an appointment |
142 | |NLG | faq_close_time | inform closing hours |
143 | |NLG | faq_open_time | inform opening hours |
144 | |NLG | faq_operating_hours | inform range of day in which service is open |
145 | |NLG | further_requests | ask if there are any further requests |
146 | |NLG | inform_schedule_inspection | system is finding possible slots for appointments |
147 | |NLG | intro_assistant_1 | introductory message presentation |
148 | |NLG | intro_assistant_2 | give options of possible services |
149 | |NLG | new_user_profile_brand_model_year | create profile for new user |
150 | |NLG | no_dates_available | no dates available for making appointments |
151 | |NLG | no_dates_available_try_new_transportation_type | no dates available for making appointments with this transportation type |
152 | |NLG | no_more_schedule_appointments | do not recognize the given date as an existing appointment |
153 | |NLG | no_pre_existing_schedule | no appointments pre-scheduled. |
154 | |NLG | offer_to_schedule | ask if user wants to schedule an appointment |
155 | |NLG | operating_hour_and_ask_for_schedule | specify possible ranges of time to schedule appointment |
156 | |NLG | propose_date | propose date for appointment |
157 | |NLG | propose_earliest_time | propose earliest possible time for scheduling appointment |
158 | |NLG | propose_other_transportation_of_device | propose other type of transportation such as waiting for the service or leaving phone |
159 | |NLG | reconfirm_date_scheduled | reconfirm time of appointment scheduled |
160 | |NLG | retrieve_user_information | ask phone number to find user profile |
161 | |NLG | schedule_or_cancel | ask again type of service required |
162 | |NLG | silence | wait in silence |
163 | |NLG | time_asked_unavailable_propose_new | proposed date is unavailable, propose a new option |
164 | |NLG | transportation_of_device | ask if user will wait suring service, dropoff phone or request pick up service |
165 | |NLG | transportation_type_unavailable | transportation type such as waiting for the service of leaving phone is not available |
166 | |NLG | working_on_previous_request | still processing previous request |
167 | |NLU | ask_for_transportation_types | ask possible options of transportation of cellphone to be serviced |
168 | |NLU | cancel | cancel existing appointment |
169 | |NLU | confirm | agree |
170 | |NLU | inconclusive | uncertainty in statement |
171 | |NLU | inform | inform |
172 | |NLU | negate | disagree |
173 | |NLU | noise | noise in user's side of conversation |
174 | |NLU | other | other cases |
175 | |NLU | rephrase | ask to repeat question |
176 | |NLU | reschedule | ask to reschedule appointment |
177 | |NLU | salutation | greeting |
178 | |NLU | schedule | ask to schedule an appointment |
179 | |NLU | transfer_agent | ask to trasnfer to a human agent |
180 | |NLU | unregistered_user | user is not yet registered in the database |
181 | |NLU | urgency | indicate it is an urgent situation |
182 | |NLU | user_initial_request | indication of goal of the call |
183 | |NLU | user_proposed_date | propose a specific date for appointment |
184 |
185 |
186 | ### Collection Methodology
187 | This dataset was extracted from real conversations between June 11 and August 29 of 2022.
188 |
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