- Description:
MC-TACO is a dataset of 13k question-answer pairs that require temporal commonsense comprehension. The dataset contains five temporal properties:
- duration (how long an event takes)
- temporal ordering (typical order of events)
- typical time (when an event occurs)
- frequency (how often an event occurs)
- stationarity (whether a state is maintained for a very long time or indefinitely)
We hope that this dataset can promote the future exploration of this particular class of reasoning problems.
Homepage: https://github.com/CogComp/MCTACO
Source code:
tfds.question_answering.Mctaco
Versions:
1.0.0
(default): No release notes.
Download size:
2.27 MiB
Dataset size:
3.18 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'test' |
9,442 |
'validation' |
3,783 |
- Features:
FeaturesDict({
'answer': Text(shape=(), dtype=tf.string),
'category': ClassLabel(shape=(), dtype=tf.int64, num_classes=5),
'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
'question': Text(shape=(), dtype=tf.string),
'sentence': Text(shape=(), dtype=tf.string),
})
Supervised keys (See
as_supervised
doc):None
Figure (tfds.show_examples): Not supported.
Examples (tfds.as_dataframe):
- Citation:
@inproceedings{ZKNR19,
author = {Ben Zhou, Daniel Khashabi, Qiang Ning and Dan Roth},
title = {"Going on a vacation" takes longer than "Going for a walk": A Study of Temporal Commonsense Understanding },
booktitle = {EMNLP},
year = {2019},
}