|
--- |
|
annotations_creators: [] |
|
language_creators: |
|
- found |
|
languages: |
|
- en |
|
licenses: |
|
- unknown |
|
multilinguality: |
|
- monolingual |
|
size_categories: |
|
emoji: |
|
- 100K<n<1M |
|
emotion: |
|
- 1K<n<10K |
|
hate: |
|
- 10K<n<100K |
|
irony: |
|
- 1K<n<10K |
|
offensive: |
|
- 10K<n<100K |
|
sentiment: |
|
- 10K<n<100K |
|
stance_abortion: |
|
- n<1K |
|
stance_atheism: |
|
- n<1K |
|
stance_climate: |
|
- n<1K |
|
stance_feminist: |
|
- n<1K |
|
stance_hillary: |
|
- n<1K |
|
source_datasets: |
|
emoji: |
|
- extended|other-tweet-datasets |
|
emotion: |
|
- extended|other-tweet-datasets |
|
hate: |
|
- extended|other-tweet-datasets |
|
irony: |
|
- extended|other-tweet-datasets |
|
offensive: |
|
- extended|other-tweet-datasets |
|
sentiment: |
|
- extended|other-tweet-datasets |
|
stance_abortion: |
|
- extended|other-tweet-datasets |
|
stance_atheism: |
|
- extended|other-tweet-datasets |
|
stance_climate: |
|
- extended|other-tweet-datasets |
|
stance_feminist: |
|
- extended|other-tweet-datasets |
|
stance_hillary: |
|
- extended|other-tweet-datasets |
|
task_categories: |
|
- text-classification |
|
task_ids: |
|
emoji: |
|
- multi-class-classification |
|
emotion: |
|
- multi-class-classification |
|
- sentiment-classification |
|
hate: |
|
- intent-classification |
|
irony: |
|
- multi-class-classification |
|
offensive: |
|
- intent-classification |
|
sentiment: |
|
- multi-class-classification |
|
- sentiment-classification |
|
stance_abortion: |
|
- intent-classification |
|
- multi-class-classification |
|
stance_atheism: |
|
- intent-classification |
|
- multi-class-classification |
|
stance_climate: |
|
- intent-classification |
|
- multi-class-classification |
|
stance_feminist: |
|
- intent-classification |
|
- multi-class-classification |
|
stance_hillary: |
|
- intent-classification |
|
- multi-class-classification |
|
paperswithcode_id: tweeteval |
|
--- |
|
|
|
# Dataset Card for tweet_eval |
|
|
|
## Table of Contents |
|
- [Dataset Description](#dataset-description) |
|
- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
|
- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
|
- [Data Instances](#data-instances) |
|
- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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- [Dataset Creation](#dataset-creation) |
|
- [Curation Rationale](#curation-rationale) |
|
- [Source Data](#source-data) |
|
- [Annotations](#annotations) |
|
- [Personal and Sensitive Information](#personal-and-sensitive-information) |
|
- [Considerations for Using the Data](#considerations-for-using-the-data) |
|
- [Social Impact of Dataset](#social-impact-of-dataset) |
|
- [Discussion of Biases](#discussion-of-biases) |
|
- [Other Known Limitations](#other-known-limitations) |
|
- [Additional Information](#additional-information) |
|
- [Dataset Curators](#dataset-curators) |
|
- [Licensing Information](#licensing-information) |
|
- [Citation Information](#citation-information) |
|
- [Contributions](#contributions) |
|
|
|
## Dataset Description |
|
|
|
- **Homepage:** [Needs More Information] |
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- **Repository:** [GitHub](https://github.com/cardiffnlp/tweeteval) |
|
- **Paper:** [EMNLP Paper](https://arxiv.org/pdf/2010.12421.pdf) |
|
- **Leaderboard:** [GitHub Leaderboard](https://github.com/cardiffnlp/tweeteval) |
|
- **Point of Contact:** [Needs More Information] |
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|
|
### Dataset Summary |
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|
|
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. The tasks include - irony, hate, offensive, stance, emoji, emotion, and sentiment. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits. |
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|
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### Supported Tasks and Leaderboards |
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- `text_classification`: The dataset can be trained using a SentenceClassification model from HuggingFace transformers. |
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|
|
### Languages |
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|
|
The text in the dataset is in English, as spoken by Twitter users. |
|
|
|
## Dataset Structure |
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|
|
### Data Instances |
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|
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An instance from `emoji` config: |
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|
|
``` |
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{'label': 12, 'text': 'Sunday afternoon walking through Venice in the sun with @user ️ ️ ️ @ Abbot Kinney, Venice'} |
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``` |
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An instance from `emotion` config: |
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|
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``` |
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{'label': 2, 'text': "“Worry is a down payment on a problem you may never have'. \xa0Joyce Meyer. #motivation #leadership #worry"} |
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``` |
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An instance from `hate` config: |
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|
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``` |
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{'label': 0, 'text': '@user nice new signage. Are you not concerned by Beatlemania -style hysterical crowds crongregating on you…'} |
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``` |
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An instance from `irony` config: |
|
|
|
``` |
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{'label': 1, 'text': 'seeing ppl walking w/ crutches makes me really excited for the next 3 weeks of my life'} |
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``` |
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|
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An instance from `offensive` config: |
|
|
|
``` |
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{'label': 0, 'text': '@user Bono... who cares. Soon people will understand that they gain nothing from following a phony celebrity. Become a Leader of your people instead or help and support your fellow countrymen.'} |
|
``` |
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An instance from `sentiment` config: |
|
|
|
``` |
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{'label': 2, 'text': '"QT @user In the original draft of the 7th book, Remus Lupin survived the Battle of Hogwarts. #HappyBirthdayRemusLupin"'} |
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``` |
|
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|
An instance from `stance_abortion` config: |
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|
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``` |
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{'label': 1, 'text': 'we remind ourselves that love means to be willing to give until it hurts - Mother Teresa'} |
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``` |
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An instance from `stance_atheism` config: |
|
|
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``` |
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{'label': 1, 'text': '@user Bless Almighty God, Almighty Holy Spirit and the Messiah. #SemST'} |
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``` |
|
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An instance from `stance_climate` config: |
|
|
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``` |
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{'label': 0, 'text': 'Why Is The Pope Upset? via @user #UnzippedTruth #PopeFrancis #SemST'} |
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``` |
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An instance from `stance_feminist` config: |
|
|
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``` |
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{'label': 1, 'text': "@user @user is the UK's answer to @user and @user #GamerGate #SemST"} |
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``` |
|
|
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An instance from `stance_hillary` config: |
|
|
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``` |
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{'label': 1, 'text': "If a man demanded staff to get him an ice tea he'd be called a sexists elitist pig.. Oink oink #Hillary #SemST"} |
|
``` |
|
|
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### Data Fields |
|
For `emoji` config: |
|
|
|
- `text`: a `string` feature containing the tweet. |
|
|
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- `label`: an `int` classification label with the following mapping: |
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|
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`0`: ❤ |
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|
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`1`: 😍 |
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|
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`2`: 😂 |
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|
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`3`: 💕 |
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|
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`4`: 🔥 |
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|
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`5`: 😊 |
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|
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`6`: 😎 |
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`7`: ✨ |
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`8`: 💙 |
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`9`: 😘 |
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|
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`10`: 📷 |
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`11`: 🇺🇸 |
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|
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`12`: ☀ |
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`13`: 💜 |
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|
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`14`: 😉 |
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|
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`15`: 💯 |
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|
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`16`: 😁 |
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|
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`17`: 🎄 |
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|
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`18`: 📸 |
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|
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`19`: 😜 |
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|
|
For `emotion` config: |
|
|
|
- `text`: a `string` feature containing the tweet. |
|
|
|
- `label`: an `int` classification label with the following mapping: |
|
|
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`0`: anger |
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|
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`1`: joy |
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|
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`2`: optimism |
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|
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`3`: sadness |
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|
|
For `hate` config: |
|
|
|
- `text`: a `string` feature containing the tweet. |
|
|
|
- `label`: an `int` classification label with the following mapping: |
|
|
|
`0`: non-hate |
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|
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`1`: hate |
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|
|
For `irony` config: |
|
|
|
- `text`: a `string` feature containing the tweet. |
|
|
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- `label`: an `int` classification label with the following mapping: |
|
|
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`0`: non_irony |
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|
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`1`: irony |
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|
|
For `offensive` config: |
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|
|
- `text`: a `string` feature containing the tweet. |
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|
|
- `label`: an `int` classification label with the following mapping: |
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|
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`0`: non-offensive |
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|
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`1`: offensive |
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|
|
For `sentiment` config: |
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|
|
- `text`: a `string` feature containing the tweet. |
|
|
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- `label`: an `int` classification label with the following mapping: |
|
|
|
`0`: negative |
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|
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`1`: neutral |
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|
|
`2`: positive |
|
|
|
For `stance_abortion` config: |
|
|
|
- `text`: a `string` feature containing the tweet. |
|
|
|
- `label`: an `int` classification label with the following mapping: |
|
|
|
`0`: none |
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|
|
`1`: against |
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|
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`2`: favor |
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|
|
For `stance_atheism` config: |
|
|
|
- `text`: a `string` feature containing the tweet. |
|
|
|
- `label`: an `int` classification label with the following mapping: |
|
|
|
`0`: none |
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|
|
`1`: against |
|
|
|
`2`: favor |
|
|
|
For `stance_climate` config: |
|
|
|
- `text`: a `string` feature containing the tweet. |
|
|
|
- `label`: an `int` classification label with the following mapping: |
|
|
|
`0`: none |
|
|
|
`1`: against |
|
|
|
`2`: favor |
|
|
|
For `stance_feminist` config: |
|
|
|
- `text`: a `string` feature containing the tweet. |
|
|
|
- `label`: an `int` classification label with the following mapping: |
|
|
|
`0`: none |
|
|
|
`1`: against |
|
|
|
`2`: favor |
|
|
|
For `stance_hillary` config: |
|
|
|
- `text`: a `string` feature containing the tweet. |
|
|
|
- `label`: an `int` classification label with the following mapping: |
|
|
|
`0`: none |
|
|
|
`1`: against |
|
|
|
`2`: favor |
|
|
|
|
|
|
|
### Data Splits |
|
|
|
| name | train | validation | test | |
|
| --------------- | ----- | ---------- | ----- | |
|
| emoji | 45000 | 5000 | 50000 | |
|
| emotion | 3257 | 374 | 1421 | |
|
| hate | 9000 | 1000 | 2970 | |
|
| irony | 2862 | 955 | 784 | |
|
| offensive | 11916 | 1324 | 860 | |
|
| sentiment | 45615 | 2000 | 12284 | |
|
| stance_abortion | 587 | 66 | 280 | |
|
| stance_atheism | 461 | 52 | 220 | |
|
| stance_climate | 355 | 40 | 169 | |
|
| stance_feminist | 597 | 67 | 285 | |
|
| stance_hillary | 620 | 69 | 295 | |
|
|
|
## Dataset Creation |
|
|
|
### Curation Rationale |
|
|
|
[Needs More Information] |
|
|
|
### Source Data |
|
|
|
#### Initial Data Collection and Normalization |
|
|
|
[Needs More Information] |
|
|
|
#### Who are the source language producers? |
|
|
|
[Needs More Information] |
|
|
|
### Annotations |
|
|
|
#### Annotation process |
|
|
|
[Needs More Information] |
|
|
|
#### Who are the annotators? |
|
|
|
[Needs More Information] |
|
|
|
### Personal and Sensitive Information |
|
|
|
[Needs More Information] |
|
|
|
## Considerations for Using the Data |
|
|
|
### Social Impact of Dataset |
|
|
|
[Needs More Information] |
|
|
|
### Discussion of Biases |
|
|
|
[Needs More Information] |
|
|
|
### Other Known Limitations |
|
|
|
[Needs More Information] |
|
|
|
## Additional Information |
|
|
|
### Dataset Curators |
|
|
|
Francesco Barbieri, Jose Camacho-Collados, Luis Espiinosa-Anke and Leonardo Neves through Cardiff NLP. |
|
|
|
### Licensing Information |
|
|
|
[Needs More Information] |
|
### Citation Information |
|
|
|
``` |
|
@inproceedings{barbieri2020tweeteval, |
|
title={{TweetEval:Unified Benchmark and Comparative Evaluation for Tweet Classification}}, |
|
author={Barbieri, Francesco and Camacho-Collados, Jose and Espinosa-Anke, Luis and Neves, Leonardo}, |
|
booktitle={Proceedings of Findings of EMNLP}, |
|
year={2020} |
|
} |
|
``` |
|
|
|
### Contributions |
|
|
|
Thanks to [@gchhablani](https://github.com/gchhablani) and [@abhishekkrthakur](https://github.com/abhishekkrthakur) for adding this dataset. |
|
|
