Documenting Geographically and Contextually Diverse Language Data Sources

Angelina McMillan-Major, Francesco De Toni, Zaid Alyafeai, Stella Biderman, Kimbo Chen, Gérard Dupont, Hady Elsahar, Chris Emezue, Alham Fikri Aji, Suzana Ilić, Nurulaqilla Khamis, Colin Leong, Maraim Masoud, Aitor Soroa, Pedro Ortiz Suarez, Daniel van Strien, Zeerak Talat, Yacine Jernite


Abstract
Contemporary large-scale data collection efforts have prioritized the amount of data collected to improve large language models (LLM). This quantitative approach has resulted in concerns for the rights of data subjects represented in data collections. This concern is exacerbated by a lack of documentation and analysis tools, making it difficult to interrogate these collections. Mindful of these pitfalls, we present a methodology for documentation-first, human-centered data collection. We apply this approach in an effort to train a multilingual LLM. We identify a geographically diverse set of target language groups (Arabic varieties, Basque, Chinese varieties, Catalan, English, French, Indic languages, Indonesian, Niger-Congo languages, Portuguese, Spanish, and Vietnamese, as well as programming languages) for which to collect metadata on potential data sources. We structure this effort by developing an online catalogue in English as a tool for gathering metadata through public hackathons. We present our tool and analyses of the resulting resource metadata, including distributions over languages, regions, and resource types, and discuss our lessons learned.
Anthology ID:
2024.nejlt-1.4
Volume:
Northern European Journal of Language Technology, Volume 10
Month:
December
Year:
2024
Address:
Linköping, Sweden
Editor:
Marcel Bollmann
Venue:
NEJLT
SIG:
Publisher:
Linköping University Electronic Press
Note:
Pages:
50–77
Language:
URL:
https://aclanthology.org/2024.nejlt-1.4/
DOI:
10.3384/nejlt.2000-1533.2024.5217
Bibkey:
Cite (ACL):
Angelina McMillan-Major, Francesco De Toni, Zaid Alyafeai, Stella Biderman, Kimbo Chen, Gérard Dupont, Hady Elsahar, Chris Emezue, Alham Fikri Aji, Suzana Ilić, Nurulaqilla Khamis, Colin Leong, Maraim Masoud, Aitor Soroa, Pedro Ortiz Suarez, Daniel van Strien, Zeerak Talat, and Yacine Jernite. 2024. Documenting Geographically and Contextually Diverse Language Data Sources. Northern European Journal of Language Technology, 10:50–77.
Cite (Informal):
Documenting Geographically and Contextually Diverse Language Data Sources (McMillan-Major et al., NEJLT 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.nejlt-1.4.pdf