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Russian Summer School in Information Retrieval

RuSSIR 2015: Information Retrieval pp 146–157Cite as

Construction of a Russian Paraphrase Corpus: Unsupervised Paraphrase Extraction

Part of the Communications in Computer and Information Science book series (CCIS,volume 573)

Abstract

This paper presents a crowdsourcing project on the creation of a publicly available corpus of sentential paraphrases for Russian. Collected from the news headlines, such corpus could be applied for information extraction and text summarization. We collect news headlines from different agencies in real-time; paraphrase candidates are extracted from the headlines using an unsupervised matrix similarity metric. We provide user-friendly online interface for crowdsourced annotation which is available at paraphraser.ru. There are 5181 annotated sentence pairs at the moment, with 4758 of them included in the corpus. The annotation process is going on and the current version of the corpus is freely available at http://paraphraser.ru.

Keywords

  • Russian paraphrase corpus
  • Lexical similarity metric
  • Unsupervised paraphrase extraction
  • Crowdsourcing

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Fig. 1.
Fig. 2.

Notes

  1. 1.

    This statement can only be applied to the informative news texts (the ones intended to inform, and not to persuade the reader) and not to the publicistic texts (exerting influence on the reader in the first place). A publicistic headline is often designed to attract readers’ attention. However, both publicistic and informative texts can be used as a source of paraphrases.

  2. 2.

    The latter might be of no importance for English, but they are essential for detecting Russian sentential paraphrases.

References

  1. Agirre, E., Cer, D., Diab, M., Gonzalez-Agirre, A., Guo W.: SEM 2013 shared task: semantic textual similarity. In: The Second Joint Conference on Lexical and Computational Semantics (2013)

    Google Scholar 

  2. Bannard, C., Callison-Burch, C.: Paraphrasing with bilingual parallel corpora. In: Proceedings of the 43rd Annual Meeting of the ACL, pp. 597–604 (2005)

    Google Scholar 

  3. Bernhard, D., Gurevych, I.: Answering learners’ questions by retrieving question paraphrases from social Q&A sites. In: Proceedings of the ACL 2008 3rd Workshop on Innovative Use of NLP for Building Educational Applications, pp. 44–52 (2008)

    Google Scholar 

  4. Bouma, G.: Normalized (pointwise) mutual information in collocation extraction. In: Proceedings of the Biennial GSCL Conference (2009)

    Google Scholar 

  5. Braslavski, P., Ustalov, D., Mukhin, M.: A spinning wheel for YARN: user interface for a crowdsourced thesaurus. In: Proceedings of the Demonstrations at the 14th Conference of the European Chapter of the Association for Computational Linguistics, Gothenburg, Sweden, pp. 101–104 (2014)

    Google Scholar 

  6. Burrows, S., Potthast, M., Stein, B.: Paraphrase acquisition via crowdsourcing and machine learning. ACM Trans. Intell. Syst. Technol. 4(3), 43 (2013)

    CrossRef  Google Scholar 

  7. Callison-Burch, C.: Paraphrasing and Translation. Institute for Communicating and Collaborative Systems, School of Informatics, University of Edinburgh (2007)

    Google Scholar 

  8. Chen, D.L., Dolan, W.B.: Collecting highly parallel data for paraphrase evaluation. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics, Portland, Oregon, USA, pp. 190–200 (2011)

    Google Scholar 

  9. Dzikovska, M.O., Nielsen, R., Brew, C., Leacock, C., Giampiccolo, D., Bentivogli, L., Clark, P., Dagan, I., Dang, H.T.: SemEval – 2013 Task 7: the joint student response analysis and 8th recognizing textual entailment challenge. In: Proceedings of the 7th International Workshop on Semantic Evaluation (SemEval 2013), Atlanta, Georgia, USA (2013)

    Google Scholar 

  10. Clough, P., Gaizauskas, R., Piao, S., Wilks, Y.: METER: MEasuring TExt Reuse. In: Isabelle, P. (ed.) Proceedings of the Fortieth Annual Meeting on Association for Computational Linguistics, Philadelphia, Pennsylvania, pp. 152–159 (2002)

    Google Scholar 

  11. Cohn, T., Callison-Burch, C., Lapata, M.: Constructing corpora for the development and evaluation of paraphrase systems. Comput. Linguist. Arch. 34(4), 597–614 (2008)

    CrossRef  Google Scholar 

  12. Dice, L.R.: Measures of the amount of ecologic association between species. Ecology 26(3), 297–302 (1945)

    CrossRef  Google Scholar 

  13. Dolan, W.B., Quirk, C., Brockett, C.: Unsupervised construction of large paraphrase corpora: exploiting massively parallel news sources. In: Proceedings of the 20th International Conference on Computational Linguistics, Geneva, Switzerland (2004)

    Google Scholar 

  14. Duboue, P.A., Chu-Carroll, J.: Answering the question you wish they had asked: the impact of paraphrasing for question answering. In: Proceedings of the Human Language Technology Conference of the North American Chapter of the ACL, New York, pp. 33–36 (2006)

    Google Scholar 

  15. Fernando, S., Stevenson, M.: A semantic similarity approach to paraphrase detection. In: Computational Linguistics UK (CLUK 2008) 11th Annual Research Colloqium (2008)

    Google Scholar 

  16. Fujita, A., Inui, K.: A class-oriented approach to building a paraphrase corpus. In: Proceedings of the Third International Workshop on Paraphrasing (2005)

    Google Scholar 

  17. Ganitkevitch, J., Callison-Burch, C.: The multilingual paraphrase database. In: Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC 2014). European Language Resources Association (ELRA), Reykjavik (2014)

    Google Scholar 

  18. Jaccard, P.: Étude Comparative de la Distribution Florale dans une Portion des Alpes et des Jura. Bulletin de la Société Vaudoise des Sciences Naturelles 37, 547–579 (1901)

    Google Scholar 

  19. Knight, K., Marcu, D.: Summarization beyond sentence extraction: a probabilistic approach to sentence compression. Artif. Intell. 139(1), 91–107 (2002)

    CrossRef  MathSciNet  MATH  Google Scholar 

  20. McCarthy, Ph.M., McNamara, D.S.: The user-language paraphrase corpus. In: Cross-Disciplinary Advances in Applied Natural Language Processing: Issues and Approaches, pp. 73–89 (2008)

    Google Scholar 

  21. Rus, V., Banjade, R., Lintean, M.: On paraphrase identification corpora. In: Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC 2014), pp. 2422–2429. European Language Resources Association (ELRA), Reykjavik (2014)

    Google Scholar 

  22. Sanchez-Perez, M., Sidorov, G., Gelbukh, A.: The winning approach to text alignment for text reuse detection at PAN 2014. In: Cappellato, L., Ferro, N., Halvey, M., Kraaij, W. (eds.) Notebook for PAN at CLEF 2014. CEUR Workshop Proceedings, vol. 1180, pp. 1004–1011. CEUR-WS.org (2014). ISSN: 1613-0073

    Google Scholar 

  23. Schmid, H.: Improvements in part-of-speech tagging with an application to German. In: Proceedings of the ACL SIGDAT-Workshop, Dublin, Ireland (1995)

    Google Scholar 

  24. Shimohata, M., Sumita, E., Matsumoto, Y.: Building a paraphrase corpus for speech translation. In: Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC 2004). European Language Resources Association (ELRA), Lisbon (2004)

    Google Scholar 

  25. Shinyama, Y., Sekine, S.: Paraphrase acquisition for information extraction. In: Proceedings of the Second International Workshop on Paraphrasing, vol. 16, pp. 65–71 (2003)

    Google Scholar 

  26. Vila, M., Rodriguez, H., Marti, M.A.: WRPA: a system for relational paraphrase acquisition from wikipedia. Procesamiento del Lenguaje Nat. 45, 11–19 (2010)

    Google Scholar 

  27. Wubben, S., van den Bosch, A., Krahmer, E., Marsi, E.: Clustering and matching headlines for automatic paraphrase acquisition. In: Proceedings of the 12th European Workshop on Natural Language Generation, Athens, Greece, pp. 122–125 (2009)

    Google Scholar 

  28. Xu, W., Ritter, A., Grishman, R.: Gathering and generating paraphrases from twitter with application to normalization. In: Proceedings of the Sixth Workshop on Building and Using Comparable Corpora, Sofia, Bulgaria, pp. 121–128 (2013)

    Google Scholar 

  29. Zhao, Sh., Lan, X., Liu, T., Li, Sh.: Application-driven statistical paraphrase generation. In: Proceedings of the 47th Annual Meeting of the ACL and the 4th IJCNLP of the AFNLP, Suntec, Singapore, pp. 834–842 (2009)

    Google Scholar 

  30. Abramov, N.: Slovar’ russkih synonymov I shodnyh po smislu virazheniy, 7th edn. Russkie slovari, Moscow (1999)

    Google Scholar 

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Authors and Affiliations

  1. Saint-Petersburg State University, Saint-Petersburg, Russian Federation

    Ekaterina Pronoza, Elena Yagunova & Anton Pronoza

Authors
  1. Ekaterina Pronoza
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  2. Elena Yagunova
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  3. Anton Pronoza
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Correspondence to Ekaterina Pronoza .

Editor information

Editors and Affiliations

  1. Ural Federal University , Yekaterinburg, Russia

    Pavel Braslavski

  2. University of Amsterdam, Amsterdam, The Netherlands

    Ilya Markov

  3. University of Florida , Gainsville, Florida, USA

    Panos Pardalos

  4. Eurecat , Barcelona, Spain

    Yana Volkovich

  5. National Research University Higher School of Economics, Moscow, Russia

    Dmitry I. Ignatov

  6. National Research University Higher School of Economics, Saint Petersburg, Russia

    Sergei Koltsov

  7. National Research University Higher School of Economics, Saint Petersburg, Russia

    Olessia Koltsova

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Pronoza, E., Yagunova, E., Pronoza, A. (2016). Construction of a Russian Paraphrase Corpus: Unsupervised Paraphrase Extraction. In: , et al. Information Retrieval. RuSSIR 2015. Communications in Computer and Information Science, vol 573. Springer, Cham. https://doi.org/10.1007/978-3-319-41718-9_8

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  • DOI: https://doi.org/10.1007/978-3-319-41718-9_8

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