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Dataset Summary
This is the task dataset for SemEval-2020 Task 7: Assessing Humor in Edited News Headlines.
Supported Tasks and Leaderboards
- Regression Task: In this task, given the original and the edited headline, the participant is required to predict the mean funniness of the edited headline. Success on this task is typically measured by achieving a low Mean Square Error.
- Predict the funnier of the two edited headlines: Given the original headline and two edited versions, the participant has to predict which edited version is the funnier of the two. Success on this task is typically measured by achieving a high accuracy.
Languages
English
Dataset Structure
Data Instances
For subtask-1, i.e Given the original and the edited headline, predict the mean funniness of the edited headline.
{
'id': 1183,
'original': 'Kushner to visit <Mexico/> following latest trump tirades.',
'edit': 'therapist',
'grades': '33332',
'meanGrade': 2.8
}
For subtask-2, i.e Given the original headline and two edited versions, predict which edited version is the funnier of the two.
{
'id': 1183,
'original1': 'Gene Cernan , Last <Astronaut/> on the Moon , Dies at 82',
'edit1': 'Dancer',
'grades1': '1113',
'meanGrade1': 1.2,
'original2': 'Gene Cernan , Last Astronaut on the Moon , <Dies/> at 82',
'edit2': 'impregnated',
'grades2': '30001',
'meanGrade2': 0.8,
'label': 1
}
Data Fields
For subtask-1
id
: Unique identifier of an edited headline.original
: The headline with replaced word(s) identified with the </> tag.edit
: The new word which replaces the word marked in </> tag in the original field.grades
: 'grades' are the concatenation of all the grades by different annotators.mean
is the mean of all the judges scores.
For subtask-2
id
: Unique identifier of an edited headline.original1
: The original headline with replaced word(s) identified with </> tag.edit1
: The new word which replaces the word marked in </> tag in theoriginal1
field.grades1
: The concatenation of all the grades annotated by different annotators for sentence1.meanGrade1
is the mean of all the judges scores for sentence1.original2
: The original headline with replaced word(s) identified with </> tag.edit2
: The new word which replaces the word marked in </> tag in theoriginal1
field.grades2
: The concatenation of all the grades annotated by different annotators for the sentence2.meanGrade2
is the mean of all the judges scores for sentence2.label
is 1 if sentence1 is more humourous than sentence2, 2 if sentence 2 is more humorous than sentence1, 0 if both the sentences are equally humorous
Data Splits
Sub Task | Train | Dev | Test | Funlines |
---|---|---|---|---|
Subtask-1:Regression | 9652 | 2419 | 3024 | 8248 |
Subtask-2: Funnier headline prediction | 9381 | 2355 | 2960 | 1958 |
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
Crowd-sourced the data by gamifying it as on the website funlines.co. Players rate the headlines on a scale of 0-4. Players are scored based on their editing and rating, and they are ranked on the game’s leaderboard page.
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
[More Information Needed]
Licensing Information
[More Information Needed]
Citation Information
@article{hossain2019president,
title={" President Vows to Cut< Taxes> Hair": Dataset and Analysis of Creative Text Editing for Humorous Headlines},
author={Hossain, Nabil and Krumm, John and Gamon, Michael},
journal={arXiv preprint arXiv:1906.00274},
year={2019}
}```
### Contributions
Thanks to [@saradhix](https://github.com/saradhix) for adding this dataset.
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