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Building text datasets for African languages. Every task below shares the same groundwork — these pages differ only in what is labelled and how it is evaluated.

Shared across text data

• Source selection (news, web, social media, books, religious & educational texts)
• Text cleaning & normalization (encoding, scripts, diacritics, punctuation)
• Language identification & code-switching handling
• Annotation guidelines & label schemas
• Annotator recruitment & inter-annotator agreement
• Metadata, dataset formatting & splits
• Licensing & toxic-content filtering

Tasks

• Text classification & labeling – (sentiment, emotion, hate speech, topic, intent)
• Text generation, summarization & QA – (open generation, summarization, question answering)
• Machine translation & parallel corpora – (parallel mining, alignment, human translation)
• Sequence labeling – (named-entity recognition, part-of-speech, chunking)