A CURATEd CATalog: Rethinking the Extraction of Pretraining Corpora for Mid-Resourced Languages

Jorge Palomar-Giner, José Javier Saiz, Ferran Espuña, Mario Mina, Severino Da Dalt, Joan Llop, Malte Ostendorff, Pedro Ortiz Suarez, Georg Rehm, Aitor Gonzalez-Agirre, Marta Villegas

Abstract: We present and describe two language resources in this paper: CATalog 1.0, the largest text corpus in Catalan to date, and CURATE (Corpus Utility for RAting TExt), a modular, parallelizable pipeline used for processing and scoring documents based on text quality that we have optimised to run in High Performance Cluster (HPC) environments. In the coming sections we describe our data preprocessing pipeline at length; traditional pipelines usually implement a set of binary filters such that a given document is either in or out. In our experience with Catalan, in lower-resource settings it is more practical to instead assign a document a soft score to allow for more flexible decision-making. We describe how the document score is calculated and highlight its interpretability by showing that it is significantly correlated with human judgements as obtained from a comparative judgement experiment. We additionally describe the different subcorpora that make up CATalog 1.0.