Datasets:
Sub-tasks:
semantic-similarity-classification
Multilinguality:
multilingual
Language Creators:
crowdsourced
Annotations Creators:
machine-generated
Source Datasets:
extended|other-tatoeba
License:
File size: 36,590 Bytes
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---
annotations_creators:
- machine-generated
language_creators:
- crowdsourced
language:
- af
- ar
- az
- be
- ber
- bg
- bn
- br
- ca
- cbk
- cmn
- cs
- da
- de
- el
- en
- eo
- es
- et
- eu
- fi
- fr
- gl
- gos
- he
- hi
- hr
- hu
- hy
- ia
- id
- ie
- io
- is
- it
- ja
- jbo
- kab
- ko
- kw
- la
- lfn
- lt
- mk
- mr
- nb
- nds
- nl
- orv
- ota
- pes
- pl
- pt
- rn
- ro
- ru
- sl
- sr
- sv
- tk
- tl
- tlh
- tok
- tr
- tt
- ug
- uk
- ur
- vi
- vo
- war
- wuu
- yue
license:
- cc-by-2.0
multilinguality:
- multilingual
size_categories:
- 100K<n<1M
- 10K<n<100K
- 1K<n<10K
- 1M<n<10M
- n<1K
source_datasets:
- extended|other-tatoeba
task_categories:
- text2text-generation
- translation
- text-classification
task_ids:
- semantic-similarity-classification
paperswithcode_id: tapaco
pretty_name: TaPaCo Corpus
tags:
- paraphrase-generation
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- ug
- uk
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---
# Dataset Card for TaPaCo Corpus
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [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:** [TaPaCo: A Corpus of Sentential Paraphrases for 73 Languages](https://zenodo.org/record/3707949#.X9Dh0cYza3I)
- **Paper:** [TaPaCo: A Corpus of Sentential Paraphrases for 73 Languages](https://www.aclweb.org/anthology/2020.lrec-1.848.pdf)
- **Data:** https://doi.org/10.5281/zenodo.3707949
- **Point of Contact:** [Yves Scherrer](https://blogs.helsinki.fi/yvesscherrer/)
### Dataset Summary
A freely available paraphrase corpus for 73 languages extracted from the Tatoeba database.
Tatoeba is a crowdsourcing project mainly geared towards language learners. Its aim is to provide example sentences
and translations for particular linguistic constructions and words. The paraphrase corpus is created by populating a
graph with Tatoeba sentences and equivalence links between sentences “meaning the same thing”. This graph is then
traversed to extract sets of paraphrases. Several language-independent filters and pruning steps are applied to
remove uninteresting sentences. A manual evaluation performed on three languages shows that between half and three
quarters of inferred paraphrases are correct and that most remaining ones are either correct but trivial,
or near-paraphrases that neutralize a morphological distinction. The corpus contains a total of 1.9 million
sentences, with 200 – 250 000 sentences per language. It covers a range of languages for which, to our knowledge,
no other paraphrase dataset exists.
### Supported Tasks and Leaderboards
Paraphrase detection and generation have become popular tasks in NLP
and are increasingly integrated into a wide variety of common downstream tasks such as machine translation
, information retrieval, question answering, and semantic parsing. Most of the existing datasets
cover only a single language – in most cases English – or a small number of languages. Furthermore, some paraphrase
datasets focus on lexical and phrasal rather than sentential paraphrases, while others are created (semi
-)automatically using machine translation.
The number of sentences per language ranges from 200 to 250 000, which makes the dataset
more suitable for fine-tuning and evaluation purposes than
for training. It is well-suited for multi-reference evaluation
of paraphrase generation models, as there is generally not a
single correct way of paraphrasing a given input sentence.
### Languages
The dataset contains paraphrases in Afrikaans, Arabic, Azerbaijani, Belarusian, Berber languages, Bulgarian, Bengali
, Breton, Catalan; Valencian, Chavacano, Mandarin, Czech, Danish, German, Greek, Modern (1453-), English, Esperanto
, Spanish; Castilian, Estonian, Basque, Finnish, French, Galician, Gronings, Hebrew, Hindi, Croatian, Hungarian
, Armenian, Interlingua (International Auxiliary Language Association), Indonesian, Interlingue; Occidental, Ido
, Icelandic, Italian, Japanese, Lojban, Kabyle, Korean, Cornish, Latin, Lingua Franca Nova\t, Lithuanian, Macedonian
, Marathi, Bokmål, Norwegian; Norwegian Bokmål, Low German; Low Saxon; German, Low; Saxon, Low, Dutch; Flemish, ]Old
Russian, Turkish, Ottoman (1500-1928), Iranian Persian, Polish, Portuguese, Rundi, Romanian; Moldavian; Moldovan,
Russian, Slovenian, Serbian, Swedish, Turkmen, Tagalog, Klingon; tlhIngan-Hol, Toki Pona, Turkish, Tatar,
Uighur; Uyghur, Ukrainian, Urdu, Vietnamese, Volapük, Waray, Wu Chinese and Yue Chinese
## Dataset Structure
### Data Instances
Each data instance corresponds to a paraphrase, e.g.:
```
{
'paraphrase_set_id': '1483',
'sentence_id': '5778896',
'paraphrase': 'Ɣremt adlis-a.',
'lists': ['7546'],
'tags': [''],
'language': 'ber'
}
```
### Data Fields
Each dialogue instance has the following fields:
- `paraphrase_set_id`: a running number that groups together all sentences that are considered paraphrases of each
other
- `sentence_id`: OPUS sentence id
- `paraphrase`: Sentential paraphrase in a given language for a given paraphrase_set_id
- `lists`: Contributors can add sentences to list in order to specify the original source of the data
- `tags`: Indicates morphological or phonological properties of the sentence when available
- `language`: Language identifier, one of the 73 languages that belong to this dataset.
### Data Splits
The dataset is having a single `train` split, contains a total of 1.9 million sentences, with 200 – 250 000
sentences per language
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### 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
Creative Commons Attribution 2.0 Generic
### Citation Information
```
@dataset{scherrer_yves_2020_3707949,
author = {Scherrer, Yves},
title = {{TaPaCo: A Corpus of Sentential Paraphrases for 73 Languages}},
month = mar,
year = 2020,
publisher = {Zenodo},
version = {1.0},
doi = {10.5281/zenodo.3707949},
url = {https://doi.org/10.5281/zenodo.3707949}
}
```
### Contributions
Thanks to [@pacman100](https://github.com/pacman100) for adding this dataset. |