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A Unified Sense Inventory for Word Sense Disambiguation in Polish

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Computational Science – ICCS 2022 (ICCS 2022)

Abstract

We introduce a comprehensive evaluation benchmark for Polish Word Sense Disambiguation task. The benchmark consists of 7 distinct datasets with sense annotations based on plWordNet–4.2. As far as we know, our work is a first attempt to standardise existing sense annotated data for Polish. We also follow the recent trends of neural WSD solutions and we test transfer learning models, as well as hybrid architectures combining lexico-semantic networks with neural text encoders. Finally, we investigate the impact of bilingual training on WSD performance. The bilingual model obtains new State of the Art performance in Polish WSD task.

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Notes

  1. 1.

    https://wordnetcode.princeton.edu/glosstag.shtml.

  2. 2.

    https://clarin-pl.eu/dspace/handle/11321/508.

  3. 3.

    https://clarin-pl.eu/dspace/handle/11321/891.

References

  1. Agirre, E., López de Lacalle, O., Soroa, A.: The risk of sub-optimal use of open source NLP software: UKB is inadvertently state-of-the-art in knowledge-based WSD. In: Proceedings of the Workshop for NLP Open Source Software (NLP-OSS), Melbourne, Australia (2018)

    Google Scholar 

  2. Bevilacqua, M., Navigli, R.: Breaking through the 80% glass ceiling: raising the state of the art in word sense disambiguation by incorporating knowledge graph information. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 2854–2864 (2020)

    Google Scholar 

  3. Broda, B., Marcińczuk, M., Maziarz, M., Radziszewski, A., Wardyński, A.: KPWr: towards a free corpus of Polish. In: Proceedings of the 8th International Conference on Language Resources and Evaluation. Istanbul, Turkey, May 2012

    Google Scholar 

  4. Dziob, A., Piasecki, M., Rudnicka, E.K.: plWordNet 4.1 - a linguistically motivated, corpus-based bilingual resource. In: Proceedings of the 10th Global Wordnet Conference, pp. 353–362

    Google Scholar 

  5. Hajnicz, E.: Lexico-semantic annotation of składnica treebank by means of PLWN lexical units. In: Proceedings of the 7th Global Wordnet Conference, Tartu, Estonia, January 2014

    Google Scholar 

  6. Harabagiu, S., Moldovan, D.: Knowledge processing on an extended wordnet. WordNet Electron. Lexical Database 305, 381–405 (1998)

    Google Scholar 

  7. Janz, A., Chlebus, J., Dziob, A., Piasecki, M.: Results of the PolEval 2020 shared task 3: word sense disambiguation. In: Proceedings of the PolEval 2020 Workshop, p. 65

    Google Scholar 

  8. Janz, A., Kocon, J., Piasecki, M., Zasko-Zielinska, M.: plWordNet as a basis for large emotive lexicons of Polish. In: Proceedings of Human Language Technologies as a Challenge for Computer Science and Linguistics Poznan, pp. 189–193 (2017)

    Google Scholar 

  9. Janz, A., Piasecki, M.: Word sense disambiguation based on constrained random walks in linked semantic networks. In: Proceedings of the International Conference on Recent Advances in Natural Language Processing, Varna, Bulgaria (2019)

    Google Scholar 

  10. Kędzia, P., Piasecki, M., Orlińska, M.: Word sense disambiguation based on large scale Polish CLARIN heterogeneous lexical resources. Cogn. Stud. (15) (2015)

    Google Scholar 

  11. Maziarz, M., Piasecki, M., Rudnicka, E., Szpakowicz, S., Kędzia, P.: plWordNet 3.0-a comprehensive lexical-semantic resource. In: Proceedings of COLING 2016, pp. 2259–2268 (2016)

    Google Scholar 

  12. Miller, G.A.: WordNet: An Electronic Lexical Database. MIT Press, Cambridge (1998)

    Google Scholar 

  13. Moro, A., Raganato, A., Navigli, R.: Entity linking meets word sense disambiguation: a unified approach. Trans. Assoc. Comput. Ling. 2, 231–244 (2014)

    Google Scholar 

  14. Navigli, R., Ponzetto, S.P.: BabelNet: building a very large multilingual semantic network. In: Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pp. 216–225 (2010)

    Google Scholar 

  15. Pasini, T., Raganato, A., Navigli, R.: XL-WSD: an extra-large and cross-lingual evaluation framework for word sense disambiguation. In: Proceedings of the AAAI Conference on Artificial Intelligence. AAAI Press (2021)

    Google Scholar 

  16. Pease, A.: Ontology - A Practical Guide. Articulate Software Press, Angwin (2011)

    Google Scholar 

  17. Ponzetto, S.P., Navigli, R.: Knowledge-rich word sense disambiguation rivaling supervised systems. In: Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pp. 1522–1531 (2010)

    Google Scholar 

  18. Raganato, A., Camacho-Collados, J., Navigli, R.: Word sense disambiguation: a unified evaluation framework and empirical comparison. In: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, vol. 1. pp. 99–110 (2017)

    Google Scholar 

  19. Rudnicka, E., Maziarz, M., Piasecki, M., Szpakowicz, S.: A strategy of mapping polish wordnet onto Princeton wordnet. In: Proceedings of COLING 2012, pp. 1039–1048 (2012)

    Google Scholar 

  20. Tan, L., Bond, F.: Building and annotating the linguistically diverse NTU-MC (NTU-multilingual corpus). In: Proceedings of the 25th Pacific Asia Conference on Language, Information and Computation, Singapore (2011)

    Google Scholar 

  21. Wang, Z., Lipton, Z.C., Tsvetkov, Y.: On negative interference in multilingual models: findings and a meta-learning treatment. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 4438–4450 (2020)

    Google Scholar 

  22. Zaśko-Zielińska, M., Piasecki, M.: Towards emotive annotation in plWordNet 4.0. In: Proceedings of the 9th Global Wordnet Conference, pp. 153–162 (2018)

    Google Scholar 

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Acknowledgment

This work was co-financed by (1) the Polish Ministry of Education and Science, CLARIN-PL; (2) the European Regional Development Fund as a part of the 2014–2020 Smart Growth Operational Programme, project number POIR.04.02.00-00C002/19; and (3) by the National Science Centre, Poland, grant number 2018/29/B/HS2/02919.

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Correspondence to Arkadiusz Janz .

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Janz, A., Dziob, A., Oleksy, M., Baran, J. (2022). A Unified Sense Inventory for Word Sense Disambiguation in Polish. In: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13351. Springer, Cham. https://doi.org/10.1007/978-3-031-08754-7_70

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  • DOI: https://doi.org/10.1007/978-3-031-08754-7_70

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