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Dataset assetOpen Source CommunityDialogue AnalysisTemporal Commonsense Reasoning

google-research-datasets/time_dial

TimeDial is an English dataset focusing on temporal commonsense reasoning in dialogue, containing approximately 1.5k carefully curated multiple‑choice cloze dialogue tasks. Extracted from DailyDialog, it challenges models with complex temporal reasoning. It includes a test set of 1,104 dialogue instances, each featuring a multiple‑choice cloze task involving temporal expressions. The dataset was annotated by English linguists.

Source
hugging_face
Created
Nov 28, 2025
Updated
Jan 18, 2024
Signals
269 views
Availability
Linked source ready
Overview

Dataset description and usage context

Dataset Overview

Basic Information

  • Name: TimeDial: Temporal Commonsense Reasoning in Dialog
  • Language: English
  • License: CC BY‑NC‑SA 4.0
  • Multilinguality: Monolingual
  • Size: 10K < n < 100K
  • Source Data: Original data
  • Task Category: Text Classification
  • Task ID: Multi‑label classification
  • Labels: dialog‑act‑classification

Dataset Structure

Data Instances

{
  "id": 1,
  "conversation": [
    "A: We need to take the accounts system offline to carry out the upgrade . But dont worry , it wont cause too much inconvenience . Were going to do it over the weekend .",
    "B: How long will the system be down for ?",
    "A: Well be taking everything offline in about two hours  time . Itll be down for a minimum of twelve hours . If everything goes according to plan , it should be up again by 6 pm on Saturday .",
    "B: Thats fine . Weve allowed <MASK> to be on the safe side ."
  ],
  "correct1": "forty-eight hours",
  "correct2": "50 hours ",
  "incorrect1": "two hours ",
  "incorrect1_rule": "Rule 1",
  "incorrect2": "12 days ",
  "incorrect2_rule": "Rule 2"
}

Data Fields

  • id: Unique identifier, integer type
  • conversation: Dialogue context containing a token, string type
  • correct1: First correct fill, string type
  • correct2: Second correct fill provided by annotators, string type
  • incorrect1: First incorrect option, string type
  • incorrect1_rule: Rule for the first incorrect option, string type
  • incorrect2: Second incorrect option, string type
  • incorrect2_rule: Rule for the second incorrect option, string type

Data Splits

  • Test set: 1,104 dialogue instances, each with two correct and two incorrect options

Dataset Creation

Data Collection and Annotation

  • Source: DailyDialog dataset
  • Annotation process:
    1. Identify dialogues rich in temporal expressions.
    2. Ask human annotators to provide correct and incorrect options.
  • Annotators: English linguists

Usage Notes

  • License: CC BY‑NC‑SA 4.0
  • Citation:
@inproceedings{qin-etal-2021-timedial,
    title = "{TimeDial: Temporal Commonsense Reasoning in Dialog}",
    author = "Qin, Lianhui and Gupta, Aditya and Upadhyay, Shyam and He, Luheng and Choi, Yejin and Faruqui, Manaal",
    booktitle = "Proc. of ACL",
    year = "2021"
}
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