ArticleData in brief2024
In the heart of Swahili: An exploration of data collection methods and corpus curation for natural language processing.
Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed.
- Swahili questions and answers dataset for aflatoxin knowledge domain.Data in brief · 2025Article
- In the heart of Swahili: An exploration of data collection methods and corpus curation for natural language processing.Data in brief · 2024Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Swahili corpus is a dataset generated by collecting written Kiswahili sentences from different sectors that deals with Kiswahili documents. Corpus of intended language is needed in Natural Language Processing (NLP) task to fit algorithm in order to understand that language before training the model. Swahili corpus dataset generated contained 1,693,228 sentences with 39,639,824 words and 871,452 unique words. Corpus exported in text file format with storage size of 168 MB. These sentences collected from different sources in different categories as follows: - Health (AFYA), Business and Industries (BIASHARA), Parliament (BUNGE), Religion (DINI), Education (ELIMU), News (HABARI), Agriculture (KILIMO), Social Media (MITANDAO), Non-Governmental Organizations (MASHIRIKA YA KIRAIA), Government (SERIKALI), Laws (SHERIA) and Politics (SIASA).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.