# Open Subtitles Paraphrase Corpus for Six Languages

arXiv: https://arxiv.org/abs/1809.06142 · HTML: https://mlsanity.com/paper/1809.06142/

## Key facts

- Cited by 24 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Sep 2018.

## Built on by (most cited first, 24 of 24)

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- [Finnish Paraphrase Corpus](https://mlsanity.com/paper/2103.13103/) (2021)
- [LAMPAT: Low-Rank Adaption for Multilingual Paraphrasing Using Adversarial Training](https://mlsanity.com/paper/2401.04348/) (2024)
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- [Improving Social Meaning Detection with Pragmatic Masking and Surrogate Fine-Tuning](https://mlsanity.com/paper/2108.00356/) (2021)
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- [Exploiting Twitter as Source of Large Corpora of Weakly Similar Pairs for Semantic Sentence Embeddings](https://mlsanity.com/paper/2110.02030/) (2021)
- [Decay No More: A Persistent Twitter Dataset for Learning Social Meaning](https://mlsanity.com/paper/2204.04611/) (2022)
- [Extracting and filtering paraphrases by bridging natural language inference and paraphrasing](https://mlsanity.com/paper/2111.07119/) (2021)
- [Multilingual Coreference Resolution in Multiparty Dialogue](https://mlsanity.com/paper/2208.01307/) (2022)
- [Quantitative Evaluation of Alternative Translations in a Corpus of Highly Dissimilar Finnish Paraphrases](https://mlsanity.com/paper/2105.02477/) (2021)
- [Paraphrase Acquisition from Image Captions](https://mlsanity.com/paper/2301.11030/) (2023)
- [A Self-enhancement Multitask Framework for Unsupervised Aspect Category Detection](https://mlsanity.com/paper/2311.09708/) (2023)
- [Closing the Operational Gap in Semantic Caching](https://mlsanity.com/paper/2606.19719/) (2026)
- [Dialogue You Can Trust: Human and AI Perspectives on Generated Conversations](https://mlsanity.com/paper/2409.01808/) (2024)
- [When Babies Teach Babies: Can student knowledge sharing outperform Teacher-Guided Distillation on small datasets?](https://mlsanity.com/paper/2411.16487/) (2024)
- [Beyond BLEU: A Case for Redefining Sign Language Translation Benchmarks](https://mlsanity.com/paper/2609.03734/) (2026)

## Abstract (arXiv)

This paper accompanies the release of Opusparcus, a new paraphrase corpus for six European languages: German, English, Finnish, French, Russian, and Swedish. The corpus consists of paraphrases, that is, pairs of sentences in the same language that mean approximately the same thing. The paraphrases are extracted from the OpenSubtitles2016 corpus, which contains subtitles from movies and TV shows. The informal and colloquial genre that occurs in subtitles makes such data a very interesting language resource, for instance, from the perspective of computer assisted language learning. For each target language, the Opusparcus data have been partitioned into three types of data sets: training, development and test sets. The training sets are large, consisting of millions of sentence pairs, and have been compiled automatically, with the help of probabilistic ranking functions. The development and test sets consist of sentence pairs that have been checked manually; each set contains approximately 1000 sentence pairs that have been verified to be acceptable paraphrases by two annotators.