PARADIGM: Paraphrase Diagnostics through Grammar Matching

Paraphrase evaluation is typically done either manually or through indirect, taskbased evaluation. We introduce an intrinsic evaluation PARADIGM which measures the goodness of paraphrase collections that are represented using synchronous grammars. We formulate two measures that evaluate these paraphrase grammars using gold standard sentential paraphrases drawn from a monolingual parallel corpus. The first measure calculates how often a paraphrase grammar is able to synchronously parse the sentence pairs in the corpus. The second measure enumerates paraphrase rules from the monolingual parallel corpus and calculates the overlap between this reference paraphrase collection and the paraphrase resource being evaluated. We demonstrate the use of these evaluation metrics on paraphrase collections derived from three different data types: multiple translations of classic French novels, comparable sentence pairs drawn from different newspapers, and bilingual parallel corpora. We show that PARADIGM correlates with human judgments more strongly than BLEU on a task-based evaluation of paraphrase quality.