Datasets:
language:
- ca
- en
multilinguality:
- multilingual
pretty_name: CA-EN Parallel Corpus
size_categories:
- 10M<n<100M
task_categories:
- translation
task_ids: []
license: cc-by-4.0
Dataset Card for CA-EN Parallel Corpus
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
Dataset Summary
The CA-EN Parallel Corpus is a Catalan-English dataset of 14.385.296 parallel sentences. The dataset was created to support Catalan in NLP tasks, specifically Machine Translation.
Supported Tasks and Leaderboards
The dataset can be used to train Bilingual Machine Translation models between English and Catalan in any direction, as well as Multilingual Machine Translation models.
Languages
The sentences included in the dataset are in Catalan (CA) and English (EN).
Dataset Structure
Data Instances
The dataset is a single tsv file where each row contains a parallel sentence pair and additional domain and text type information for each sentence. Datafields are separated by , Text delimiter is "
Data Fields
Each example contains the following fields:
- sentence_id: unique alphanumeric sentence identifier
- en: ENGLISH
- en_sentence: English sentence
- ca: CATALAN
- ca_sentence: Catalan sentence
- domain: sentence domain
- text_type: sentence text type
Example:
[
{
"00000a47-e4a5-8ab6-e0fa-3cbbeb596f34","en","As for the search engines, they also rely on the structure of your information content on the website to analyze and index your website.","ca","Pel que fa als motors de cerca, també es basen en l'estructura del seu contingut d'informació al lloc web per analitzar i indexar el seu lloc web.","MWM","SM"
},
...
]
####List of domains
AUT: Automotive, transport, traffic regulations LEG: legal, law, HR, certificates, degrees MWM: Marketing, web, merchandising, customer support and service, e-commerce , advertising, surveys LSM: Medicine, natural sciences, food/nutrition, biology, sexology, cosmetics, chemistry, genetics ENV: Environment, agriculture, forestry, fisheries, farming, zoology, ecology FIN: Finance, economics, business, entrepreneurship, business, competitions, labour, employment, accounting, insurance, insurance POL: Politics, international relations, European Union, international organisations, defence, military PRN: Porn, inappropriate content COM: Computers, IT, robotics, domotics, home automation, telecommunications ING: Pure engineering (mechanical, electrical, electronic, aerospace...), meteorology, mining, engineering, maritime, acoustics ARC: Architecture, civil engineering, construction, public engineering MAT: Mathematics, statistics, physics HRM: History, religion, mythology, folklore, philosophy, psychology, ethics, anthropology, tourism CUL: Art, poetry, literature, cinema, video games, theatre, theatre/film scripts, esotericism, astrology, sports, music, photography GEN: General - generic cathegory with topics such as clothing, textiles, gastronomy, etc.
####List of text types
PAT: Patents SM: Social Media (social networks, chats, forums, tweets...) CON: Vernacular (transcription of conversations, subtitles) EML: Emails MNL: Manuals, data sheets NEW: News, journalism GEN: Prose, generic type of text
Data Splits
The dataset contains a single split: train.
Dataset Creation
Curation Rationale
This dataset is aimed at promoting the development of Machine Translation between Catalan and other languages, specifically English.
Source Data
Initial Data Collection and Normalization
The data is a brand new collection of parallel sentences in Catalan and English, partially derived from web crawlings and belonging to a mix of different domains and styles. The source data is Catalan authentic text translated to English or authentic English text translated to Catalan.
The data was obtained through a combination of human translation and machine translation with human proofreading. After the translation process, the data was deduplicated and filtered to remove any sentence pairs with a cosine similarity of less than 0.75 in order to improve the data alignment quality. This was done using sentence embeddings calculated using LaBSE. The obtained cleaned corpus consists of 14.385.296 parallel sentences of human quality.
Who are the source language producers?
The original data gathering was entrusted to an external company through a public tender process.
Annotations
Annotation process
The dataset does not contain any annotations.
Who are the annotators?
[N/A]
Personal and Sensitive Information
No anonymisation process was performed.
Considerations for Using the Data
Social Impact of Dataset
By providing this resource, we intend to promote the use of Catalan across NLP tasks, thereby improving the accessibility and visibility of the Catalan language.
Discussion of Biases
No specific bias mitigation strategies were applied to this dataset. Inherent biases may exist within the data.
Other Known Limitations
The dataset contains data of several specific domains. Application of this dataset in other domains would be of limited use.
Additional Information
Dataset Curators
Language Technologies Unit at the Barcelona Supercomputing Center (langtech@bsc.es).
This work has been promoted and financed by the Generalitat de Catalunya through the Aina project.
Licensing Information
This work is licensed under a Creative Commons Attribution 4.0 International license(https://creativecommons.org/licenses/by/4.0/).
Citation Information
[N/A]
Contributions
[N/A]