Testing gradient measures of relevance in discourse

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We experimentally test two information-theoretic measures of relevance: Entropy reduction (van Rooy, 2004; Rothe et al. 2018), and KL-divergence (Nelson et al., 2010; Hawkinset al., 2015). Results show that KL-divergence fits introspective relevance judgments better than entropy reduction. However, neither measure is adequate on its own.

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