metadata

language:
  - en
license:
  - apache-2.0
multilinguality:
  - monolingual
pretty_name: WOZ 2.0
size_categories:
  - 1K<n<10K
task_categories:
  - conversational

Dataset Card for WOZ 2.0

Repository: https://github.com/nmrksic/neural-belief-tracker/tree/master/data/woz
Paper: https://aclanthology.org/P17-1163.pdf
Leaderboard: None
Who transforms the dataset: Qi Zhu(zhuq96 at gmail dot com)

To use this dataset, you need to install ConvLab-3 platform first. Then you can load the dataset via:

from convlab.util import load_dataset, load_ontology, load_database

dataset = load_dataset('woz')
ontology = load_ontology('woz')
database = load_database('woz')

For more usage please refer to here.

Dataset Summary

Describe the dataset.

How to get the transformed data from original data:
- download woz_[train|validate|test]_en.json from https://github.com/nmrksic/neural-belief-tracker/tree/master/data/woz and save to woz dir in the current directory.
- Run python preprocess.py in the current directory.
Main changes of the transformation:
- domain is set to restaurant.
- normalize the value of categorical slots in state and dialogue acts.
- belief_states in WOZ dataset contains request intents, which are ignored in processing.
- use simple string match to find value spans of non-categorical slots.
Annotations:
- User dialogue acts, state

Supported Tasks and Leaderboards

NLU, DST, E2E

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	600	4472	7.45	11.37	1	100	-	100	96.56
validation	200	1460	7.3	11.28	1	100	-	100	95.52
test	400	2892	7.23	11.49	1	100	-	100	94.83
all	1200	8824	7.35	11.39	1	100	-	100	95.83

1 domains: ['restaurant']

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{mrksic-etal-2017-neural,
    title = "Neural Belief Tracker: Data-Driven Dialogue State Tracking",
    author = "Mrk{\v{s}}i{\'c}, Nikola  and
      {\'O} S{\'e}aghdha, Diarmuid  and
      Wen, Tsung-Hsien  and
      Thomson, Blaise  and
      Young, Steve",
    booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/P17-1163",
    doi = "10.18653/v1/P17-1163",
    pages = "1777--1788",
}

Licensing Information

Apache License, Version 2.0