Elamur Research⌕
☰
home / papers / 2023 / Investigating Explicitation of Discourse Connectives in Translation using Automatic Annotations

Investigating Explicitation of Discourse Connectives in Translation using Automatic Annotations

Summary

Translators frequently insert, drop, or rework discourse connectives such as because or however, and earlier studies found a general drift toward explicitation. Those studies depended on manual annotation, so they examined only a few connectives and small samples. This paper tests whether automatic tools can support a much broader analysis of English–German translation in both directions, using parliamentary proceedings from the Europarl Direct corpus. Connectives are detected and sense-labelled with language-specific discourse parsers (Discopy for English, the German Shallow Discourse Parser for German). They are then linked across languages with the Awesome Align neural word aligner.

Beyond counting insertions and omissions, the authors measure how specific a connective is through relative entropy over relation senses, normalised within each language. This lets them detect cases where a translation uses a more or less specific connective than the source. Even after offsetting implicitation in the reverse direction, translations remain clearly more explicit, both through added connectives and through more specific ones. English connectives also prove less specific overall than German ones. The study shows that automatic annotation makes large-scale discourse translation research practical.

Key points

  • Data: 33 Europarl Direct proceedings were used.
    • About 171k tokens of English originals with German translations (18 proceedings).
    • About 95k tokens of German originals with English translations (15 proceedings).
  • Tools and reported performance:
    • Discopy (English) follows the PDTB 2.0 sense scheme and reports 97.20% accuracy for connective identification.
    • The German Shallow Discourse Parser is BERT-based, uses DimLex knowledge, and is trained on PCC 2.2 with PDTB 3.0 senses. It reports 87.57% accuracy for identifying discourse usage.
    • Awesome Align reports a 15.1% alignment error rate on English–German data, outperforming GIZA++ and eflomal.
  • Scale: The study covers over 300 connective types and more than 18,000 aligned instances.
    • English: 173 types and 8,058 tokens.
    • German: 126 types and 9,739 tokens.
  • Domain effect: Qualitative analysis points to a likely genre influence. The sources are speeches prepared for oral delivery, while the translations are written for reading. For example, but is often rendered as the more formal doch/jedoch.
  • Data availability: The automatically aligned and annotated dataset is publicly released on OSF.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

Fields: Linguistics & languages

Topics: Discourse analysis

Cite

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.18653/v1/2023.sigdial-1.2

@inproceedings{yung2023investigating,
  title = {{Investigating Explicitation of Discourse Connectives in Translation using Automatic Annotations}},
  author = {Yung, Frances and Scholman, Merel and Lapshinova-Koltunski, Ekaterina and Pollkläsener, Christina and Demberg, Vera},
  booktitle = {Proceedings of the 24th Annual Meeting of the Special Interest Group on Discourse and Dialogue},
  year = {2023},
  doi = {10.18653/v1/2023.sigdial-1.2},
  url = {https://doi.org/10.18653/v1/2023.sigdial-1.2}
}

References

33 references, 8 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Jet Hoek, Jacqueline Evers-Vermeul, and Ted JM Sanders. 2015. The role of expectedness in the implicitation and explicitation of discourse relations. In Proceedings of the Second Workshop on Discourse in Machine Translation, pages 41–46. find our card
  2. Viktor Becher. 2010. Towards a more rigorous treatment of the explicitation hypothesis in translation studies. Trans-kom, 3(1):1–25. find
  3. Viktor Becher. 2011a. Explicitation and implicitation in translation. A corpus-based study of English-German and German-English translations of business texts. Ph.D. thesis, Staats-und Universitätsbibliothek Hamburg Carl von Ossietzky. find
  4. Jet Hoek, Sandrine Zufferey, Jacqueline Evers-Vermeul, and Ted JM Sanders. 2017. Cognitive complexity and the linguistic marking of coherence relations: A parallel corpus study. Journal of pragmatics, 121:113–131. find
  5. Viktor Becher. 2011b. When and why do translators add connectives?: A corpus-based study. Target. International Journal of Translation Studies, 23(1):26–47. find
  6. Juliane House. 1997. Translation quality assessment: A model revisited. Gunter Narr Verlag. find
  7. Sh Blum-Kulka. 1986. Shifts of cohesion and coherence in translation. Interlingual and Intercultural Communication. Discourse and Cognition in Translation and Second Language Acquisition Studies, pages 17–35. find
  8. Juliane House. 2004. Explicitness in discourse across languages. Bochum: AKS. find
  9. Juliane House. 2014. Translation quality assessment: Past and present. Springer. find
  10. Peter Bourgonje. 2021. Shallow discourse parsing for German, volume 351. IOS Press. find
  11. Kinga Klaudy. 1998. Explicitation. Routledge encyclopedia of translation studies, pages 80–84. find
  12. Peter Bourgonje, Yulia Grishina, and Manfred Stede. 2017. Toward a bilingual lexical database on connectives: Exploiting a german/italian parallel corpus. find
  13. Kinga Klaudy. 2009. The asymmetry hypothesis in translation research. Translators and their readers. In Homage to Eugene A. Nida. Brussels: Les Editions du Hazard, 283:303. find
  14. Peter Bourgonje and Manfred Stede. 2018. Identifying explicit discourse connectives in german. In Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue, pages 327–331. find our card
  15. René Knaebel. 2021. discopy: A neural system for shallow discourse parsing. In Proceedings of the 2nd Workshop on Computational Approaches to Discourse, pages 128–133. find our card
  16. Peter Bourgonje and Manfred Stede. 2020. The potsdam commentary corpus 2.2: Extending annotations for shallow discourse parsing. In Proceedings of the 12th Language Resources and Evaluation Conference, pages 1061–1066. find our card
  17. Majid Laali. 2017. Inducing discourse resources using annotation projection. Ph.D. thesis, Concordia University. find
  18. Ekaterina Lapshinova-Koltunski, Christina Pollkläsener, and Heike Przybyl. 2022. Exploring explicitation and implicitation in parallel interpreting and translation corpora. The Prague Bulletin of Mathematical Linguistics, (119):5–22. find
  19. Bruno Cartoni and Thomas Meyer. 2012. Extracting directional and comparable corpora from a multilingual corpus for translation studies. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC’12), CONF, pages 2132–2137. find
  20. Josep Marco. 2018. Connectives as indicators of explicitation in literary translation: A study based on a comparable and parallel corpus. Target. International Journal of Translation Studies, 30(1):87–111. find
  21. Ludivine Crible, Ágnes Abuczki, Nijolė Burkšaitienė, Péter Furkó, Anna Nedoluzhko, Sigita Rackevičienė, Franz Josef Och and Hermann Ney. 2000. Improved statistical alignment models. In Proceedings of the 38th annual meeting of the association for computational linguistics, pages 440–447. find our card
  22. Sandrine Zufferey and Bruno Cartoni. 2014. A multifactorial analysis of explicitation in translation. Target. International Journal of Translation Studies, 26(3):361–384. find
  23. Robert Östling and Jörg Tiedemann. 2016. Efficient word alignment with Markov Chain Monte Carlo. Prague Bulletin of Mathematical Linguistics, 106:125–146. find
  24. Sibel Özer, Murathan Kurfalı, Deniz Zeyrek, Amália Mendes, and Giedrė Valūnaitė Oleškevičienė. 2022. Linking discourse-level information and the induction of bilingual discourse connective lexicons. Semantic Web, (Preprint):1–22. find
  25. Rashmi Prasad, Nikhil Dinesh, Alan Lee, Eleni Milt-sakaki, Livio Robaldo, Aravind K Joshi, and Bonnie L Webber. 2008. The penn discourse treebank 2.0. In LREC. find our card
  26. Hernán Robledo and Rogelio Nazar. 2023. A proposal for the inductive categorisation of parenthetical discourse markers in spanish using parallel corpora. International Journal of Corpus Linguistics. find
  27. Merel Scholman, Dong Tianai, Frances Yung, and Vera Demberg. 2022. Discogem: A crowdsourced corpus of genre-mixed implicit discourse relations. In the 13th Language Resources and Evaluation Conference (LREC 2022), pages 3281–3290. European Language Resources Association. find our card
  28. Henny Sluyter-Gäthje, Peter Bourgonje, and Manfred Stede. 2020. Shallow discourse parsing for under-resourced languages: Combining machine translation and annotation projection. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 1044–1050. find our card
  29. Manfred Stede. 2002. Dimlex: A lexical approach to discourse markers. A. Lenci and, 501:1–15. find
  30. Yannick Versley. 2010. Discovery of ambiguous and unambiguous discourse connectives via annotation projection. In Proceedings of Workshop on Annotation and Exploitation of Parallel Corpora (AEPC), pages 83–82. find
  31. Bonnie Webber, Rashmi Prasad, Alan Lee, and Aravind Joshi. 2019. The penn discourse treebank 3.0 annotation manual. Philadelphia, University of Pennsylvania, 35:108. find
  32. Deniz Zeyrek, Amalia Mendes, Yulia Grishina, Murathan Kurfali, Samuel Gibbon, and Maciej Ogrodniczuk. 2019. Ted multilingual discourse bank (ted-mdb): a parallel corpus annotated in the pdtb style. Language Resources and Evaluation, pages 1–38. find
  33. Sandrine Zufferey. 2016. Discourse connectives across languages: Factors influencing their explicit or implicit translation. Languages in Contrast. International Journal for Contrastive Linguistics, 16(2):264– 279. find

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/papers/yung-2023-investigating-explicitation-discourse-connectives-translation/