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Automatic language identification is frequentlyframed as a multi-class classification problem.However, when creating digital corpora forless commonly written languages, it may bemore appropriate to consider it a data min-ing problem. For these varieties, one knowsahead of time that the vast majority of doc-uments are of little interest. By minimizingresources spent on classifying such documents,we can create corpora covering previously over-looked languages faster than existing pipelines.To demonstrate the effectiveness of the tar-geted mining perspective, we introduce a newpipeline that can filter a single snapshot in twohours. We also provide web corpora for severalFrench-based Creoles.