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The First Shared Task on Discourse Representation Structure Parsing

What it is about

The shared task asked participants to parse short English texts into Discourse Representation Structures (DRSs), given in clausal form. Each entity is a discourse referent with a WordNet concept, roles come from VerbNet, and presuppositions and scope are explicit. Scoring compares the sets of clauses that a system outputs with the gold clauses. Five systems took part, using recurrent networks, transformers, transition-based parsing and graph decoders. The top systems beat the previous state of the art. The authors name the next steps: longer texts, where they expect simple sequence-to-sequence models to struggle, harder phenomena such as ellipsis, comparatives and multiword expressions, and languages other than English.

Ideas

For Mova

The code is tools/translate/measure.rs (scoring) and meta.rs. I1 is a measure rather than a method, and I2 is a test of how the reader behaves outside single verses, which open problem 1 (attachment noise) makes relevant.

Topics: Discourse analysis · Machine translation

Cite

The paper itself, not this card. BibTeX from the library's record of the work. DOI 10.18653/v1/w19-1201 · arXiv 2005.13399

@inproceedings{abzianidze2019first,
  title = {{The First Shared Task on Discourse Representation Structure Parsing}},
  author = {Abzianidze, Lasha and Noord, Rik van and Haagsma, Hessel and Bos, Johan},
  booktitle = {Proceedings of the IWCS Shared Task on Semantic Parsing},
  year = {2019},
  doi = {10.18653/v1/w19-1201},
  eprint = {2005.13399},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.18653/v1/w19-1201}
}

References

44 references, 2 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Abzianidze, L., J. Bjerva, K. Evang, H. Haagsma, R. van Noord, P. Ludmann, D.-D. Nguyen, and J. Bos (2017, April). The Parallel Meaning Bank: Towards a multilingual corpus of translations annotated with compositional meaning representations. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, Valencia, Spain, pp. 242–247. Association for Computational Linguistics. find our card
  2. Abzianidze, L. and J. Bos (2017, September). Towards universal semantic tagging. In Proceedings of the 12th International Conference on Computational Semantics (IWCS 2017) – Short Papers, Montpellier, France. Association for Computational Linguistics. find
  3. Allen, J. F., M. Swift, and W. de Beaumont (2008). Deep Semantic Analysis of Text. In J. Bos and R. Delmonte (Eds.), Semantics in Text Processing. STEP 2008 Conference Proceedings, Volume 1 of Research in Computational Semantics, pp. 343–354. College Publications. find
  4. Asher, N. and A. Lascarides (2003). Logics of conversation. Studies in natural language processing. Cambridge University Press. find
  5. Basile, V. and J. Bos (2013). Aligning formal meaning representations with surface strings for wide-coverage text generation. In Proceedings of the 14th European Workshop on Natural Language Generation, Sofia, Bulgaria, pp. 1–9. find
  6. Bjerva, J., J. Bos, R. Van der Goot, and M. Nissim (2014). The meaning factory: Formal semantics for recognizing textual entailment and determining semantic similarity. In Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014), Dublin, Ireland, pp. 642–646. find
  7. Blackburn, P. and J. Bos (2005). Representation and Inference for Natural Language. A First Course in Computational Semantics. CSLI. find
  8. Bonial, C., W. J. Corvey, M. Palmer, V. Petukhova, and H. Bunt (2011). A hierarchical unification of LIRICS and VerbNet semantic roles. In Proceedings of the 5th IEEE International Conference on Semantic Computing (ICSC 2011), pp. 483–489. find
  9. Bos, J. (2008). Wide-Coverage Semantic Analysis with Boxer. In J. Bos and R. Delmonte (Eds.), Semantics in Text Processing. STEP 2008 Conference Proceedings, Volume 1 of Research in Computational Semantics, pp. 277–286. College Publications. find
  10. Bos, J. (2015). Open-domain semantic parsing with Boxer. In B. Megyesi (Ed.), Proceedings of the 20th Nordic Conference of Computational Linguistics (NODALIDA 2015), pp. 301–304. find
  11. Bos, J. (2016). Expressive power of Abstract Meaning Representations. Computational Linguistics 42(3), 527–535. find
  12. Bos, J. (2017, September). Indexicals and compositionality: Inside-out or outside-in? In Proceedings of the 12th International Conference on Computational Semantics (IWCS 2017) – Short Papers, Montpellier, France. Association for Computational Linguistics. find
  13. Bos, J., S. Clark, M. Steedman, J. R. Curran, and J. Hockenmaier (2004). Wide-coverage semantic representations from a CCG parser. In Proceedings of the 20th International Conference on Computational Linguistics (COLING 2004), Geneva, Switzerland, pp. 1240–1246. find
  14. Bos, J. and K. Markert (2005). Recognising textual entailment with logical inference. In Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, pp. 628–635. find our card
  15. Cai, S. and K. Knight (2013, August). Smatch: an evaluation metric for semantic feature structures. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Sofia, Bulgaria, pp. 748–752. Association for Computational Linguistics. find
  16. Dagan, I., D. Roth, M. Sammons, and F. M. Zanzotto (2013). Recognizing Textual Entailment: Models and Applications. Synthesis Lectures on Human Language Technologies. Morgan & Claypool Publishers. find
  17. Dyer, C., A. Kuncoro, M. Ballesteros, and N. A. Smith (2016). Recurrent neural network grammars. In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 199–209. find
  18. Evang, K. (2019). Transition-based DRS parsing using stack-LSTMs. In Proceedings of the IWCS 2019 Shared Task on Semantic Parsing. find
  19. Fellbaum, C. (Ed.) (1998). WordNet. An Electronic Lexical Database. Cambridge, Ma., USA: The MIT Press. find
  20. Groschwitz, J., M. Lindemann, M. Fowlie, M. Johnson, and A. Koller (2018). Amr dependency parsing with a typed semantic algebra. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 1831–1841. find
  21. Hershcovich, D., Z. Aizenbud, L. Choshen, E. Sulem, A. Rappoport, and O. Abend (2019). Semeval 2019 task 1: Cross-lingual semantic parsing with UCCA. find
  22. Junczys-Dowmunt, M., R. Grundkiewicz, T. Dwojak, H. Hoang, K. Heafield, T. Neckermann, F. Seide, U. Germann, A. Fikri Aji, N. Bogoychev, A. F. T. Martins, and A. Birch (2018, July). Marian: Fast neural machine translation in C++. In Proceedings of ACL 2018, System Demonstrations, Melbourne, Australia, pp. 116–121. Association for Computational Linguistics. find
  23. Kamp, H. and U. Reyle (1993). From Discourse to Logic; An Introduction to Modeltheoretic Semantics of Natural Language, Formal Logic and DRT. Dordrecht: Kluwer. find
  24. Klein, G., Y. Kim, Y. Deng, J. Senellart, and A. Rush (2017). OpenNMT: Open-source toolkit for neural machine translation. In Proceedings of ACL 2017, System Demonstrations, Vancouver, Canada, pp. 67–72. Association for Computational Linguistics. find
  25. Le, P. and W. Zuidema (2012). Learning compositional semantics for open domain semantic parsing. In Proceedings of COLING 2012, Mumbai, India, pp. 1535–1552. find
  26. The COLING 2012 Organizing Committee. find
  27. Liu, J., S. Cohen, and M. Lapata (2019). Discourse representation structure parsing with recurrent neural networks and the transformer model. In Proceedings of the IWCS 2019 Shared Task on Semantic Parsing. find
  28. Liu, J., S. B. Cohen, and M. Lapata (2018). Discourse representation structure parsing. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Volume 1, Melbourne, Australia, pp. 429–439. find
  29. Marelli, M., S. Menini, M. Baroni, L. Bentivogli, R. Bernardi, and R. Zamparelli (2014). A sick cure for the evaluation of compositional distributional semantic models. In N. Calzolari, K. Choukri, T. Declerck, H. Loftsson, B. Maegaard, J. Mariani, A. Moreno, J. Odijk, and S. Piperidis (Eds.), Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14), Reykjavik, Iceland. European Language Resources Association (ELRA). find
  30. May, J. (2016, June). Semeval-2016 task 8: Meaning representation parsing. In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), San Diego, California, pp. 1063– 1073. Association for Computational Linguistics. find
  31. May, J. and J. Priyadarshi (2017, August). Semeval-2017 task 9: Abstract meaning representation parsing and generation. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), Vancouver, Canada, pp. 536–545. Association for Computational Linguistics. find
  32. Nissim, M., L. Abzianidze, K. Evang, R. van der Goot, H. Haagsma, B. Plank, and M. Wieling (2017). Sharing is caring: The future of shared tasks. Computational Linguistics 43(4), 897–904. find
  33. Noreen, E. W. (1989). Computer-intensive Methods for Testing Hypotheses. Wiley New York. find
  34. Oepen, S., M. Kuhlmann, Y. Miyao, D. Zeman, S. Cinkova, D. Flickinger, J. Hajic, and Z. Uresova (2015, June). SemEval 2015 task 18: Broad-coverage semantic dependency parsing. In Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), Denver, Colorado, pp. 915–926. Association for Computational Linguistics. find
  35. Oepen, S., M. Kuhlmann, Y. Miyao, D. Zeman, D. Flickinger, J. Hajic, A. Ivanova, and Y. Zhang (2014, August). SemEval 2014 task 8: Broad-coverage semantic dependency parsing. In Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014), Dublin, Ireland, pp. 63–72. Association for Computational Linguistics. find
  36. Pennington, J., R. Socher, and C. Manning (2014). GloVe: Global vectors for word representation. In Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP), Doha, Qatar, pp. 1532–1543. find
  37. Van der Sandt, R. A. (1992). Presupposition projection as anaphora resolution. Journal of Semantics 9(4), 333–377. find
  38. Van Noord, R. (2019). Neural Boxer at the IWCS shared task on DRS parsing. In Proceedings of the IWCS 2019 Shared Task on Semantic Parsing. find
  39. van Noord, R., L. Abzianidze, H. Haagsma, and J. Bos (2018). Evaluating scoped meaning representations. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), Miyazaki, Japan. find
  40. Van Noord, R., L. Abzianidze, A. Toral, and J. Bos (2018). Exploring neural methods for parsing discourse representation structures. Transactions of the Association for Computational Linguistics 6, 619–633. find
  41. van Noord, R. and J. Bos (2017). Neural semantic parsing by character-based translation: Experiments with Abstract Meaning Representations. Computational Linguistics in the Netherlands Journal 7, 93–108. find
  42. Van Noord, R., A. Toral, and J. Bos (2019). Linguistic information in neural semantic parsing with multiple encoders. In IWCS 2019-13th International Conference on Computational Semantics-Short papers. find
  43. Vaswani, A., N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin (2017). Attention is all you need. In Advances in neural information processing systems, pp. 5998– 6008. find
  44. Venhuizen, N. J., J. Bos, P. Hendriks, and H. Brouwer (2018). Discourse semantics with information structure. Journal of Semantics. find

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