mlsanityData to 7 Oct 2026

Open Subtitles Paraphrase Corpus for Six Languages

arXiv 1809.06142 ↗First posted 17 Sep 2018cs.CLcited by 24

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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.

Key facts. Cited by 24 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Sep 2018.

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Citing papers per year: 2021: 7; 2022: 5; 2023: 4; 2024: 5; 2025: 1; 2026: 2.

24 papers.

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  1. 2022IndicNLG Benchmark: Multilingual Datasets for Diverse NLG Tasks in Indic Languagescited by 42
  2. 2022GEMv2: Multilingual NLG Benchmarking in a Single Line of Codecited by 36
  3. 2024SemEval-2024 Shared Task 6: SHROOM, a Shared-task on Hallucinations and Related Observable Overgeneration Mistakescited by 24
  4. 2021Exploring Text-to-Text Transformers for English to Hinglish Machine Translation with Synthetic Code-Mixingcited by 16
  5. 2022BanglaParaphrase: A High-Quality Bangla Paraphrase Datasetcited by 15
  6. 2023Exploring Methods for Cross-lingual Text Style Transfer: The Case of Text Detoxificationcited by 15
  7. 2023A Call for Standardization and Validation of Text Style Transfer Evaluationcited by 13
  8. 2021Finnish Paraphrase Corpuscited by 10
  9. 2024LAMPAT: Low-Rank Adaption for Multilingual Paraphrasing Using Adversarial Trainingcited by 8
  10. 2024MTEB-French: Resources for French Sentence Embedding Evaluation and Analysiscited by 6
  11. 2025Redefining Machine Translation on Social Network Services with Large Language Modelscited by 6
  12. 2021Improving Social Meaning Detection with Pragmatic Masking and Surrogate Fine-Tuningcited by 5
12 more
  1. 2021The Current State of Finnish NLPcited by 5
  2. 2021Exploiting Twitter as Source of Large Corpora of Weakly Similar Pairs for Semantic Sentence Embeddingscited by 3
  3. 2022Decay No More: A Persistent Twitter Dataset for Learning Social Meaningcited by 3
  4. 2021Extracting and filtering paraphrases by bridging natural language inference and paraphrasingcited by 2
  5. 2022Multilingual Coreference Resolution in Multiparty Dialoguecited by 2
  6. 2021Quantitative Evaluation of Alternative Translations in a Corpus of Highly Dissimilar Finnish Paraphrasescited by 1
  7. 2023Paraphrase Acquisition from Image Captionscited by 1
  8. 2023A Self-enhancement Multitask Framework for Unsupervised Aspect Category Detectioncited by 1
  9. 2026Closing the Operational Gap in Semantic Cachingcited by 1
  10. 2024Dialogue You Can Trust: Human and AI Perspectives on Generated Conversationscited by 0
  11. 2024When Babies Teach Babies: Can student knowledge sharing outperform Teacher-Guided Distillation on small datasets?cited by 0
  12. 2026Beyond BLEU: A Case for Redefining Sign Language Translation Benchmarkscited by 0