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Your team is currently engaged in an NLP research project aimed at predicting the political affiliations of authors based on the articles they have authored. The training dataset for this project is extensive and structured as follows: AuthorA : Political Party A TextA1 : [ SentenceA11 , SentenceA12 , SentenceA13 , ...] TextA2 : [ SentenceA21 , SentenceA22 , SentenceA23 , ...] … AuthorB : Political Party B TextB1 : [ SentenceB11 , SentenceB12 , SentenceB13 , ...] TextB2 : [ SentenceB21 , SentenceB22 , SentenceB23 , ...] … AuthorC : Political Party B TextC1 : [ SentenceC11 , SentenceC12 , SentenceC13 , ...] TextC2 : [ SentenceC21 , SentenceC22 , SentenceC23 , ...] … AuthorD : Political Party A TextD1 : [ SentenceD11 , SentenceD12 , SentenceD13 , ...] TextD2 : [ SentenceD21 , SentenceD22 , SentenceD23 , ...] … … To maintain the standard 80%-10%-10% data distribution across the training, testing, and evaluation subsets, you should distribute the training examples as follows: