Mova0.5 pre-release⌕
☰
home / docs / papers / Machine translation / Cross-lingual Semantic Representation for NLP with UCCA

Cross-lingual Semantic Representation for NLP with UCCA

What it is about

A tutorial abstract on UCCA (Universal Conceptual Cognitive Annotation), a meaning scheme meant to apply across languages without language-specific lexical resources. Its unit is the scene, which describes an action, movement or state, and it is somewhat like a FrameNet frame. A graph of units is anchored to the tokens, and edges carry a small set of coarse categories: process, state, participant, adverbial, linker, relator, functional element and others. Corpora exist in English, German and French, and annotation is under way in Russian and Hebrew. The paper argues that UCCA is stable across translation, because it keeps the structure that translations usually preserve. The tutorial covers the guidelines, the parsers, the CoNLL and SemEval shared tasks, and applications to simplification and evaluation. The text has no experiments.

Ideas

For Mova

The coarse category set is the argument for keeping the meta-world's tags small. The scene idea links to prag, and the stability check in I3 is a measure for tools/translate/src/measure.rs. The paper gives no measured results of its own, so the ideas stay as tests to run. They bear on open problem 4, which concerns which boundaries and function words become features.

Topics: Machine translation

Cite

The paper itself, not this card. BibTeX from the library's record of the work. DOI 10.18653/v1/2020.coling-tutorials.1

@inproceedings{abend2020cross,
  title = {{Cross-lingual Semantic Representation for NLP with UCCA}},
  author = {Abend, Omri and Dvir, Dotan and Hershcovich, Daniel and Prange, Jakob and Schneider, Nathan},
  booktitle = {Proceedings of the 28th International Conference on Computational Linguistics: Tutorial Abstracts},
  year = {2020},
  doi = {10.18653/v1/2020.coling-tutorials.1},
  url = {https://doi.org/10.18653/v1/2020.coling-tutorials.1}
}

References

67 references, 15 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Omri Abend and Ari Rappoport. 2013. Universal Conceptual Cognitive Annotation (UCCA). In Proc. of ACL, pages 228–238, August. find our card
  2. Omri Abend and Ari Rappoport. 2017. The state of the art in semantic representation. In Proc. of ACL, pages 77–89. find
  3. Omri Abend, Shai Yerushalmi, and Ari Rappoport. 2017. UCCAApp: Web-application for syntactic and semantic phrase-based annotation. Proc. of ACL System Demonstrations, pages 109–114. find
  4. Fernando Alva-Manchego, Louis Martin, Carolina Scarton, and Lucia Specia. 2019. EASSE: Easier Automatic Sentence Simplification Evaluation. In To Appear in EMNLP-ICJNLP 2019: System Demonstrations, Hong Kong, China, November. find
  5. Ofir Arviv, Ruixiang Cui, and Daniel Hershcovich. 2020. HUJI-KU at MRP 2020: Two transition-based neural parsers. In Proceedings of the CoNLL 2020 Shared Task: Cross-Framework Meaning Representation Parsing, pages 73 – 82, Online. find
  6. Hongxiao Bai and Hai Zhao. 2019. SJTU at MRP 2019: A transition-based multi-task parser for cross-framework meaning representation parsing. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Computational Natural Language Learning, pages 86 – 94, Hong Kong, China. find
  7. Collin F. Baker, Charles J. Fillmore, and John B. Lowe. 1998. The Berkeley FrameNet project. In ACL-COLING ’98. find our card
  8. Laura Banarescu, Claire Bonial, Shu Cai, Madalina Georgescu, Kira Griffitt, Ulf Hermjakob, Kevin Knight, Martha Palmer, and Nathan Schneider. 2013. Abstract Meaning Representation for sembanking. In Proc. of the Linguistic Annotation Workshop. find our card
  9. Alexandra Birch, Omri Abend, Ondřej Bojar, and Barry Haddow. 2016. HUME: Human UCCA-based evaluation of machine translation. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pages 1264–1274, Austin, Texas, November. Association for Computational Linguistics. find our card
  10. Lars Borin, Markus Forsberg, and Benjamin Lyngfelt. 2013. 2) close encounters of the fifth kind: Some linguistic and computational aspects of the Swedish FrameNet++ project. Veredas-Revista de Estudos Linguísticos, 17(1-). find
  11. Jie Cao, Yi Zhang, Adel Youssef, and Vivek Srikumar. 2019. Amazon at MRP 2019: Parsing meaning representations with lexical and phrasal anchoring. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Computational Natural Language Learning, pages 138 – 148, Hong Kong, China. find
  12. Rich Caruana. 1997. Multitask Learning. Machine Learning, 28(1):41–75, jul. find
  13. Wanxiang Che, Longxu Dou, Yang Xu, Yuxuan Wang, Yijia Liu, and Ting Liu. 2019. HIT-SCIR at MRP 2019: A unified pipeline for meaning representation parsing via efficient training and effective encoding. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Computational Natural Language Learning, pages 76 – 85, Hong Kong, China. https://github.com/nschneid/amr-tutorial/ ↗
  14. Yufei Chen, Yajie Ye, and Weiwei Sun. 2019. Peking at MRP 2019: Factorization- and composition-based parsing for Elementary Dependency Structures. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Computational Natural Language Learning, pages 166 – 176, Hong Kong, China. find
  15. Leshem Choshen and Omri Abend. 2018. Automatic metric validation for grammatical error correction. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1372–1382, Melbourne, Australia, July. Association for Computational Linguistics. find
  16. William Croft, Dawn Nordquist, Katherine Looney, and Michael Regan. 2017. Linguistic typology meets universal dependencies. In TLT, pages 63–75. find
  17. Ruixiang Cui and Daniel Hershcovich. 2020. Refining implicit argument annotation for UCCA. In Proc. of DMR. find
  18. Dun Deng and Nianwen Xue. 2017. Translation divergences in chinese–english machine translation: An empirical investigation. Computational Linguistics, 43(3):521–565. find our card
  19. R.M.W. Dixon. 2005. A Semantic Approach to English Grammar. Oxford University Press, Oxford. find
  20. Robert M. W. Dixon. 2010/2012. Basic Linguistic Theory. Oxford University Press. find
  21. Marianne Djemaa, Marie Candito, Philippe Muller, and Laure Vieu. 2016. Corpus annotation within the French FrameNet: a domain-by-domain methodology. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16), pages 3794–3801, Portorož, Slovenia, May. European Language Resources Association (ELRA). find
  22. Lucia Donatelli, Meaghan Fowlie, Jonas Groschwitz, Alexander Koller, Matthias Lindemann, Mario Mina, and Pia WeiSSenhorn. 2019. Saarland at MRP 2019: Compositional parsing across all graphbanks. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Computational Natural Language Learning, pages 66 – 75, Hong Kong, China. find
  23. Longxu Dou, Yunlong Feng, Yuqiu Ji, Wanxiang Che, and Ting Liu. 2020. HIT-SCIR at MRP 2020: Transition-based parser and iterative inference parser. In Proceedings of the CoNLL 2020 Shared Task: Cross-Framework Meaning Representation Parsing, pages 65 – 72, Online. find
  24. Kira Droganova, Andrey Kutuzov, Nikita Mediankin, and Daniel Zeman. 2019. ÚFAL–Oslo at MRP 2019: Garage sale semantic parsing. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Computational Natural Language Learning, pages 158 – 165, Hong Kong, China. find
  25. Avi Hayoun and Michael Elhadad. 2016. The Hebrew FrameNet project. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16), pages 4341–4347, Portorož, Slovenia, May. European Language Resources Association (ELRA). find our card
  26. Daniel Hershcovich and Ofir Arviv. 2019. TUPA at MRP 2019: A multi-task baseline system. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Computational Natural Language Learning, pages 28 – 39, Hong Kong, China. find
  27. Daniel Hershcovich, Omri Abend, and Ari Rappoport. 2017. A transition-based directed acyclic graph parser for UCCA. In Proc. of ACL, pages 1127–1138. find
  28. Daniel Hershcovich, Omri Abend, and Ari Rappoport. 2018. Multitask parsing across semantic representations. In Proc. of ACL, pages 373–385. find
  29. Daniel Hershcovich, Omri Abend, and Ari Rappoport. 2019a. Content differences in syntactic and semantic representation. In Proc. of NAACL-HLT. find
  30. Daniel Hershcovich, Leshem Choshen, Elior Sulem, Zohar Aizenbud, Ari Rappoport, and Omri Abend. 2019b. SemEval 2019 task 1: Cross-lingual semantic parsing with UCCA. In Proc. of SemEval. find
  31. Daniel Hershcovich, Nathan Schneider, Dotan Dvir, Jakob Prange, Miryam de Lhoneux, and Omri Abend. 2020. Comparison by conversion: Reverse-engineering UCCA from syntax and lexical semantics. In Proc. of COL-ING. find our card
  32. Wei Jiang, Zhenghua Li, Yu Zhang, and Min Zhang. 2019. HLT@SUDA at SemEval-2019 Task 1: UCCA graph parsing as constituent tree parsing. In Proc. of SemEval, pages 11–15, Minneapolis, Minnesota, USA, June. find
  33. Eliyahu Kiperwasser and Yoav Goldberg. 2016. Simple and accurate dependency parsing using bidirectional LSTM feature representations. Transactions of the Association for Computational Linguistics, 4:313–327. find our card
  34. Alexander Koller, Stephan Oepen, and Weiwei Sun. 2019. Graph-based meaning representations: Design and processing. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts, pages 6–11, Florence, Italy, July. Association for Computational Linguistics. find
  35. Yuta Koreeda, Gaku Morio, Terufumi Morishita, Hiroaki Ozaki, and Kohsuke Yanai. 2019. Hitachi at MRP 2019: Unified encoder-to-biaffine network for cross-framework meaning representation parsing. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Computational Natural Language Learning, pages 114 – 126, Hong Kong, China. find
  36. Sunny Lai, Chun Hei Lo, Kwong Sak Leung, and Yee Leung. 2019. CUHK at MRP 2019: Transition-based parser with cross-framework variable-arity resolve action. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Computational Natural Language Learning, pages 104 – 113, Hong Kong, China. find
  37. Bin Li, Yuan Wen, Weiguang Qu, Lijun Bu, and Nianwen Xue. 2016. Annotating the little prince with Chinese AMRs. In Proceedings of the 10th Linguistic Annotation Workshop held in conjunction with ACL 2016 (LAW-X 2016), pages 7–15, Berlin, Germany, August. Association for Computational Linguistics. find
  38. Zuchao Li, Hai Zhao, Zhuosheng Zhang, Rui Wang, Masao Utiyama, and Eiichiro Sumita. 2019. SJTU–NICT at MRP 2019: Multi-task learning for end-to-end uniform semantic graph parsing. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Computational Natural Language Learning, pages 45 – 54, Hong Kong, China. find
  39. Weimin Lyu, Sheng Huang, Abdul Rafae Khan, Shengqiang Zhang, Weiwei Sun, and Jia Xu. 2019. CUNY-PKU parser at SemEval-2019 task 1: Cross-lingual semantic parsing with UCCA. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 92–96, Minneapolis, Minnesota, USA, June. Association for Computational Linguistics. find
  40. David Mareček, Ondřej Bojar, Ondřej Hübsch, Rudolf Rosa, and Dušan Variš. 2017. CUNI experiments for WMT17 metrics task. In Proceedings of the Second Conference on Machine Translation, pages 604–611, Copenhagen, Denmark, September. Association for Computational Linguistics. find
  41. Gabriel Marzinotto, Johannes Heinecke, and Géraldine Damnati. 2019. MaskParse@deskin at SemEval-2019 task 1: Cross-lingual UCCA semantic parsing using recursive masked sequence tagging. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 107–112, Minneapolis, Minnesota, USA, June. Association for Computational Linguistics. find
  42. Joakim Nivre, Marie-Catherine de Marneffe, Filip Ginter, Jan Hajič, Christopher D. Manning, Sampo Pyysalo, Sebastian Schuster, Francis Tyers, and Daniel Zeman. 2020. Universal Dependencies v2: An evergrowing multilingual treebank collection. In Proceedings of the 12th Language Resources and Evaluation Conference, pages 4034–4043, Marseille, France, May. European Language Resources Association. find our card
  43. Stephan Oepen, Omri Abend, Jan Hajič, Daniel Hershcovich, Marco Kuhlmann, Tim O’Gorman, Nianwen Xue, Jayeol Chun, Milan Straka, and Zdeňka Urešová. 2019. MRP 2019: Cross-framework Meaning Representation Parsing. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Computational Natural Language Learning, pages 1 – 27, Hong Kong, China. find
  44. Stephan Oepen, Omri Abend, Lasha Abzianidze, Johan Bos, Jan Hajič, Daniel Hershcovich, Bin Li, Tim O’Gorman, Nianwen Xue, and Daniel Zeman. 2020. MRP 2020: The Second Shared Task on Cross-framework and Cross-Lingual Meaning Representation Parsing. In Proceedings of the CoNLL 2020 Shared Task: Cross-Framework Meaning Representation Parsing, pages 1 – 22, Online. find
  45. Kyoko Hirose Ohara, Seiko Fujii, Hiroaki Saito, Shun Ishizaki, Toshio Ohori, and Ryoko Suzuki. 2003. The Japanese FrameNet project: A preliminary report. In Proceedings of pacific association for computational linguistics, pages 249–254. Citeseer. find
  46. Martha Palmer, Daniel Gildea, and Paul Kingsbury. 2005. The proposition bank: An annotated corpus of semantic roles. Computational Linguistics, 31(1). find our card
  47. Jungyeul Park, Sejin Nam, Youngsik Kim, Younggyun Hahm, Dosam Hwang, and Key-Sun Choi. 2014. Frame-semantic web: a case study for Korean. In International Semantic Web Conference (Posters & Demos), pages 257–260. find
  48. Hao Peng, Sam Thomson, and Noah A. Smith. 2017. Deep multitask learning for semantic dependency parsing. In Proc. of ACL, pages 2037–2048. find
  49. Jakob Prange, Nathan Schneider, and Omri Abend. 2019a. Made for each other: Broad-coverage semantic structures meet preposition supersenses. In Proc. of CoNLL. To appear., November. find
  50. Jakob Prange, Nathan Schneider, and Omri Abend. 2019b. Semantically constrained multilayer annotation: The case of coreference. In Proceedings of the First International Workshop on Designing Meaning Representations (DMR), pages 164–176, Florence, Italy, August. Association for Computational Linguistics. find
  51. Tobias Pütz and Kevin Glocker. 2019. Tüpa at SemEval-2019 task1: (almost) feature-free semantic parsing. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 113–118, Minneapolis, Minnesota, USA, June. Association for Computational Linguistics. find
  52. David Samuel and Milan Straka. 2020. ÚFAL at MRP 2020: Permutation-invariant semantic parsing in PERIN. In Proceedings of the CoNLL 2020 Shared Task: Cross-Framework Meaning Representation Parsing, pages 53 – 64, Online. find
  53. Nathan Schneider, Jeffrey Flanigan, and Tim O’Gorman. 2015. The logic of AMR: practical, unified, graph-based sentence semantics for NLP. In Proc. of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Tutorial Abstracts, pages 4–5, Denver, Colorado, USA, May. find
  54. Milan Straka and Jana Straková. 2019. ÚFAL MRPipe at MRP 2019: UDPipe goes semantic in the Meaning Representation Parsing shared task. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Computational Natural Language Learning, pages 127 – 137, Hong Kong, China. find
  55. Elior Sulem, Omri Abend, and Ari Rappoport. 2015. Conceptual annotations preserve structure across translations: A French-English case study. In Proc. of S2MT, pages 11–22. find
  56. Elior Sulem, Omri Abend, and Ari Rappoport. 2018a. Semantic structural evaluation for text simplification. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pages 685–696, New Orleans, Louisiana, June. Association for Computational Linguistics. find our card
  57. Elior Sulem, Omri Abend, and Ari Rappoport. 2018b. Simple and effective text simplification using semantic and neural methods. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 162–173, Melbourne, Australia, July. Association for Computational Linguistics. find our card
  58. Elior Sulem, Omri Abend, and Ari Rappoport. 2020. Semantic structural decomposition for neural machine translation. In Proc. of *SEM. find
  59. Shiva Taslimipoor, Omid Rohanian, and Sara Može. 2019. GCN-sem at SemEval-2019 task 1: Semantic parsing using graph convolutional and recurrent neural networks. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 102–106, Minneapolis, Minnesota, USA, June. Association for Computational Linguistics. find
  60. Dang Tuan Nguyen and Trung Tran. 2019. DANGNT@UIT.VNU-HCM at SemEval 2019 task 1: Graph transformation system from Stanford basic dependencies to Universal Conceptual Cognitive Annotation (UCCA). In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 97–101, Minneapolis, Minnesota, USA, June. Association for Computational Linguistics. find our card
  61. Aaron Steven White, Drew Reisinger, Keisuke Sakaguchi, Tim Vieira, Sheng Zhang, Rachel Rudinger, Kyle Rawlins, and Benjamin Van Durme. 2016. Universal decompositional semantics on Universal Dependencies. In Proc. of EMNLP, pages 1713–1723. find our card
  62. Jin Xu, Yinuo Guo, and Junfeng Hu. 2020. Incorporate semantic structures into machine translation evaluation via ucca. find our card
  63. Liping You and Kaiying Liu. 2005. Building Chinese FrameNet database. 2005 International Conference on Natural Language Processing and Knowledge Engineering, pages 301–306. find
  64. Dian Yu and Kenji Sagae. 2019. UC Davis at SemEval-2019 task 1: DAG semantic parsing with attention-based decoder. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 119–124, Minneapolis, Minnesota, USA, June. Association for Computational Linguistics. find
  65. Sheng Zhang, Xutai Ma, Rachel Rudinger, Kevin Duh, and Benjamin Van Durme. 2018. Cross-lingual decompositional semantic parsing. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 1664–1675. find
  66. Sheng Zhang, Xutai Ma, Kevin Duh, and Benjamin Van Durme. 2019a. Broad-coverage semantic parsing as transduction. In Proc. of EMNLP-IJCNLP. To appear., November. find
  67. Yue Zhang, Wei Jiang, Qingrong Xia, Junjie Cao, Rui Wang, Zhenghua Li, and Min Zhang. 2019b. SUDA– Alibaba at MRP 2019: Graph-based models with BERT. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Computational Natural Language Learning, pages 149 – 157, Hong Kong, China. find

This page in Markdown → https://md.mova.elamur.ai/free/en/docs/papers/abend-2020-cross-lingual-semantic-representation-nlp/