OSPT: European Portuguese Paraphrastic Dataset with Machine Translation

Abstract

We describe OSPT, a new linguistic resource for European Portuguese that comprises more than 1.5 million Portuguese-Portuguese sentential paraphrase pairs. We generated the pairs automatically by using neural machine translation to translate the non-Portuguese side of a large parallel corpus. We hope this new corpus can be a valuable resource for paraphrase generation and provide a rich semantic knowledge source to improve downstream natural language understanding tasks. To show the quality and utility of such a dataset, we use it to train paraphrastic sentence embeddings and evaluate them in the ASSIN2 semantic textual similarity (STS) competition. We found that semantic embeddings trained on a small subset of OSPT can produce better semantic embeddings than the ones trained in the finely curated ASSIN2's training data. Additionally, we show OSPT can be used for paraphrase generation with the potential to produce good data augmentation systems that pseudo-translate from Brazilian Portuguese to European Portuguese.