# Dataset Card for KVRET - **Repository:** https://nlp.stanford.edu/blog/a-new-multi-turn-multi-domain-task-oriented-dialogue-dataset/ - **Paper:** https://arxiv.org/pdf/1705.05414.pdf - **Leaderboard:** None - **Who transforms the dataset:** Qi Zhu(zhuq96 at gmail dot com) ### Dataset Summary In an effort to help alleviate this problem, we release a corpus of 3,031 multi-turn dialogues in three distinct domains appropriate for an in-car assistant: calendar scheduling, weather information retrieval, and point-of-interest navigation. Our dialogues are grounded through knowledge bases ensuring that they are versatile in their natural language without being completely free form. - **How to get the transformed data from original data:** - Run `python preprocess.py` in the current directory. - **Main changes of the transformation:** - Create user `dialogue acts` and `state` according to original annotation. - Put dialogue level kb into system side `db_results`. - Skip repeated turns and empty dialogue. - **Annotations:** - user dialogue acts, state, db_results. ### Supported Tasks and Leaderboards NLU, DST, Context-to-response ### Languages English ### Data Splits | split | dialogues | utterances | avg_utt | avg_tokens | avg_domains | cat slot match(state) | cat slot match(goal) | cat slot match(dialogue act) | non-cat slot span(dialogue act) | |------------|-------------|--------------|-----------|--------------|---------------|-------------------------|------------------------|--------------------------------|-----------------------------------| | train | 2424 | 12720 | 5.25 | 8.02 | 1 | - | - | - | 98.07 | | validation | 302 | 1566 | 5.19 | 7.93 | 1 | - | - | - | 97.62 | | test | 304 | 1627 | 5.35 | 7.7 | 1 | - | - | - | 97.72 | | all | 3030 | 15913 | 5.25 | 7.98 | 1 | - | - | - | 97.99 | 3 domains: ['schedule', 'weather', 'navigate'] - **cat slot match**: how many values of categorical slots are in the possible values of ontology in percentage. - **non-cat slot span**: how many values of non-categorical slots have span annotation in percentage. ### Citation ``` @inproceedings{eric-etal-2017-key, title = "Key-Value Retrieval Networks for Task-Oriented Dialogue", author = "Eric, Mihail and Krishnan, Lakshmi and Charette, Francois and Manning, Christopher D.", booktitle = "Proceedings of the 18th Annual {SIG}dial Meeting on Discourse and Dialogue", year = "2017", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/W17-5506", } ``` ### Licensing Information TODO