Volume 18, Issue 1 (Journal of Control, V.18, N.1 Spring 2024)
JoC 2024, 18(1): 13-43 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Tohidi N, Dadkhah C, Gelbukh A. Abstract Meaning Representation: A State-of-the-Art Review. JoC 2024; 18 (1) :13-43
URL: http://joc.kntu.ac.ir/article-1-1044-en.html
URL: http://joc.kntu.ac.ir/article-1-1044-en.html
1- Artificial Engineering Depatement, Faculty of Computer Engineering, K. N. Toosi University of Technology, Tehran, Iran
2- CIC, Instituto Politécnico Nacional
2- CIC, Instituto Politécnico Nacional
Abstract: (184 Views)
The application of Abstract Meaning Representation (AMR) is widely increasing as a principal form of structured sentence semantics, and it is considered as a turning point for Natural Language Processing (NLP) research. AMRs are rooted and labeled graphs, which capture semantics on sentence level and abstract away from Morpho-Syntactic properties. The nodes of the graph represent meaning concepts, and the edge labels show relationships between them. In this paper, we give a brief review about the existing approaches of generating text from AMR and parsing input text to produce AMR by studying various research from 2013 to 2022. Besides, we explain how the researchers have been used AMR for prevalent NLP tasks. Afterwards, we describe the existing datasets and evaluation metrics, which can be used in this regard. Finally, we discuss some basic features and challenges of AMR.
Type of Article: Review paper |
Subject:
Special
Received: 2022/10/2 | Accepted: 2023/05/1 | Published: 2024/06/20
Received: 2022/10/2 | Accepted: 2023/05/1 | Published: 2024/06/20
References
1. [1] Marcus, Mitchell P.; Santorini, Beatrice; Marcinkiewicz, Mary Ann, "Building a Large Annotated Corpus of English: The Penn Treebank," Computational Linguistics, vol. 19, no. 2, pp. 313-330, 1993. [DOI:10.21236/ADA273556]
2. [2] Abolghasemi, Majid; Dadkhah, Chitra; Tohidi, Nasim, "HTS-DL: Hybrid Text Summarization System using Deep Learning," in The 27th International Computer Conference, the Computer Society of Iran, Tehran, Online, 2022. [DOI:10.1109/CSICC55295.2022.9780395]
3. [3] Tohidi, Nasim; Dadkhah, Chitra; Rustamov, Rustam B., "Optimizing the performance of Persian multi-objective question answering system," in 16th International Conference on "Technical and Physical Problems of Electrical Engineering", Istanbul, Online, 2020.
4. [4] Tohidi, Nasim; Hasheminejad, Seyed Mohammad Hossein;, "MOQAS: Multi-objective question answering system," Journal of Intelligent & Fuzzy Systems, vol. 36, no. 4, pp. 3495-3512, 2019. [DOI:10.3233/JIFS-181364]
5. [5] J. Flanigan, "Parsing and Generation for the Abstract Meaning Representation," Carnegie Mellon University, Pittsburgh, 2018.
6. [6] U. Weinreich, "On the Semantic Structure of Language," in On Semantics, Philadelphia, University of Pennsylvania Press, 2018, pp. 37-96.
7. [7] Basile, Valerio; Bos, Johan; Evang, Kilian; Venhuizen, Noortje, "A platform for collaborative semantic annotation," in In Proceedings of the Demonstrations at the 13th Conference of the European Chapter of the Association for Computational Linguistics., 2012.
8. [8] Butler, Alistair; Yoshimoto, Kei., "Banking Meaning Representations from Treebanks.," Linguistic Issues in Language Technology, vol. 7, no. 6, pp. 1-22, 2012. [DOI:10.33011/lilt.v7i.1269]
9. [9] Abend, O.; Rappoport A., "UCCA: A Semantics-based Grammatical Annotation Scheme.," in In Proceedings of the 10th International Conference on Computational Semantics (IWCS 2013), 2013.
10. [10] Böhmová, Alena; Hajič, Jan; Hajičová, Eva; Hladká, Barbora, The Prague dependency treebank, vol. 20, Springer, 2003, p. 103-127. [DOI:10.1007/978-94-010-0201-1_7]
11. [11] Uchida, H.; Zhu, M.; Senta, T. D., "an electronic language for communication, understanding and collaboration.," UNL: Universal Networking Language, IAS/UNU Tokyo, 1996.
12. [12] Banarescu, Laura; Bonial, Claire; Cai, Shu; Georgescu, Madalina; Griffitt, Kira; Hermjakob, Ulf; Knight, Kevin; Koehn, Philipp; Palmer, Martha; Schneider, Nathan, "Abstract Meaning Representation for Sembanking," in In proceedings of the 7th Linguistic Annotation Workshop & Interoperability with Discourse, Sofia, Bulgaria, 2013.
13. [13] Tohidi, Nasim; Dadkhah, Chitra, "Abstract Meaning Representation Applications: A Short Review," in The 1st Conference on Artificial Intelligence and Smart Computing, Online, Semnan, Iran, 2022.
14. [14] J. Bos, "Expressive Power of Abstract Meaning Representations," Computational Linguistics, vol. 42, pp. 527-535, 2016. [DOI:10.1162/COLI_a_00257]
15. [15] Cai, Shu; Knight, Kevin, "Smatch: an Evaluation Metric for Semantic Feature Structures," in In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Sofia, Bulgaria, 2013.
16. [16] Knight, Kevin; Badarau, Bianca; Baranescu, Laura; Bonial, Claire; Bardocz, Madalina; Griffitt, Kira; Hermjakob, Ulf; Marcu, Daniel; Palmer, Martha; O'Gorman, Tim; Schneider, Nathan, "Abstract Meaning Representation (AMR) Annotation Release 3.0," Linguistic Data Consortium, Philadelphia, 2020.
17. [17] Jurafsky, Daniel; Martin, James H., Speech and Language Processing, Upper Saddle River, NJUnited States: Prentice Hall, 2019.
18. [18] J. Bos, "Economical Discourse Representation Theory," in International Workshop on Controlled Natural Language, Verlag Berlin Heidelberg, 2010. [DOI:10.1007/978-3-642-14418-9_8]
19. [19] C. Wang, "Abstract Meaning Representation Parsing," PhD thesis, Brandeis University, 2018.
20. [20] Li, Bin; Wen, Yuan; Song, Li; Qu, Weiguang; Xue, Nianwen, "Building a Chinese AMR Bank with Concept and Relation Alignments," Linguistic Issues in Language Technology, vol. 18, no. 1, 2019. [DOI:10.33011/lilt.v18i.1429]
21. [21] Wein, Shira; Schneider, Nathan, "Classifying Divergences in Cross-lingual AMR Pairs," in The Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop, Punta Cana, Dominican Republic, 2021. [DOI:10.18653/v1/2021.law-1.6]
22. [22] Pustejovsky, James; Lai, Ken; Xue, Nianwen, "Modeling Quantification and Scope in Abstract Meaning Representations," in The First International Workshop on Designing Meaning Representations, Florence, Italy, 2019. [DOI:10.18653/v1/W19-3303]
23. [23] O'Gorman, Tim; Regan, Michael; Griffitt, Kira; Hermjakob, Ulf; Knight, Kevin; Palmer, Martha, "AMR Beyond the Sentence: the Multi-sentence AMR corpus," in The 27th International Conference on Computational Linguistics, Santa Fe, New Mexico, USA, 2018.
24. [24] Anikina, Tatiana; Koller, Alexander; Roth, Michael, "Predicting Coreference in Abstract Meaning Representations," in The Third Workshop on Computational Models of Reference, Anaphora and Coreference, Barcelona, Spain (online), 2020.
25. [25] Fu, Qiankun; Song, Linfeng; Du, Wenyu; Zhang, Yue, "End-to-End AMR Coreference Resolution," in The 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), Online, 2021. [DOI:10.18653/v1/2021.acl-long.324]
26. [26] Lai, Kenneth; Donatelli, Lucia; Pustejovsky, James, "A Continuation Semantics for Abstract Meaning Representation," in The Second International Workshop on Designing Meaning Representations, Barcelona, Spain (online), 2020.
27. [27] Bonn, Julia; Palmer, Martha; Cai, Zheng; Wright-Bettner, Kristin, "Spatial AMR: Expanded Spatial Annotation in the Context of a Grounded Minecraft Corpus," in The 12th Language Resources and Evaluation Conference, Marseille, France, 2020.
28. [28] Stein, Katharina; Donatelli, Lucia, "Representing Implicit Positive Meaning of Negated Statements in AMR," in The Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop, Punta Cana, Dominican Republic, 2021. [DOI:10.18653/v1/2021.law-1.3]
29. [29] Williamson, Gregor; Elliott, Patrick; Ji, Yuxin, "Intensionalizing Abstract Meaning Representations: Non-Veridicality and Scope," in The Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop, 2021. [DOI:10.18653/v1/2021.law-1.17]
30. [30] Donatelli, Lucia; Regan, Michael; Croft, William; Schneider, Nathan, "Annotation of Tense and Aspect Semantics for Sentential AMR," in The Joint Workshop on Linguistic Annotation, Multiword Expressions and Constructions (LAW-MWE-CxG-2018), Santa Fe, New Mexico, USA, 2018.
31. [31] M. F. Bakal, "Graph-to-Graph Translations To Augment Abstract Meaning Representation Tense And Aspect," University of Michigan, 2021.
32. [32] Szubert, Ida; Damonte, Marco; Cohen, Shay B.; Steedman, Mark, "The Role of Reentrancies in Abstract Meaning Representation Parsing," in Findings of the Association for Computational Linguistics: EMNLP 2020, Online, 2020. [DOI:10.18653/v1/2020.findings-emnlp.199]
33. [33] Chiang, David; Andreas, Jacob; Bauer, Daniel; Hermann, Karl Moritz; Jones, Bevan; Knight, Kevin, "Parsing graphs with hyperedge replacement grammars," in In Proceedings of the 51st Meeting of the Association of Computational Linguistics (Volume 1: Long Papers), Sofia, Bulgaria, 2013.
34. [34] Peng, Xiaochang; Song, Linfeng; Gildea, Daniel, "A synchronous hyperedge replacement grammar based approach for AMR parsing," in In Proceedings of the Nineteenth Conference on Computational Natural Language Learning, Beijing, China, 2015. [DOI:10.18653/v1/K15-1004]
35. [35] Peng, Xiaochang; Gildea, Daniel, "UofR at SemEval-2016 task 8: Learning synchronous hyperedge replacement grammar for AMR parsing," in In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), San Diego, California, 2016. [DOI:10.18653/v1/S16-1183]
36. [36] Artzi, Yoav; Lee, Kenton; Zettlemoyer, Luke, "Broad-coverage CCG semantic parsing with AMR," in In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, Lisbon, Portugal, 2015. [DOI:10.18653/v1/D15-1198]
37. [37] Flanigan, Jeffrey; Thomson, Sam; Carbonell, Jaime; Dyer, Chris; Smith. Noah A., "A Discriminative Graph-Based Parser for the Abstract Meaning Representation," in Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, Baltimore, Maryland, 2014. [DOI:10.3115/v1/P14-1134]
38. [38] Jones, Bevan; Andreas, Jacob; Bauer, Daniel; Hermann, Karl Moritz; Knight, Kevin, "Semantics-Based Machine Translation with Hyperedge Replacement Grammars," in In Proceedings of COLING., 2012.
39. [39] Pourdamghani, Nima; Gao, Yang; Hermjakob, Ulf; Knight, Kevin, "Aligning English Strings with Abstract Meaning Representation Graphs," in In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), Doha, Qatar, 2014. [DOI:10.3115/v1/D14-1048]
40. [40] Xue, Nianwen; Bojar, Ondřej; Hajič, Jan; Palmer, Martha; Urešová, Zdeňka; Zhang, Xiuhong, "Not an Interlingua, But Close: Comparison of English AMRs to Chinese and Czech," in In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), Reykjavik, Iceland, 2014.
41. [41] Werling, Keenon; Angeli, Gabor; Manning, Christopher D., "Robust Subgraph Generation Improves Abstract Meaning Representation Parsing," in In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), Beijing, China, 2015. [DOI:10.3115/v1/P15-1095]
42. [42] Flanigan, Jeffrey; Dyer, Chris; Smith, Noah A.; Carbonell, Jaime, "CMU at SemEval-2016 task 8: Graph-based AMR parsing with infinite ramp loss," in In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval- 2016), San Diego, California, 2016a. [DOI:10.18653/v1/S16-1186]
43. [43] Zhou, Junsheng; Xu, Feiyu; Uszkoreit, Hans; QU, Weiguang; Li, Ran; Gu, Yanhui, "AMR parsing with an incremental joint model," in In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, Austin, Texas, 2016. [DOI:10.18653/v1/D16-1065]
44. [44] Foland, William; Martin, James H., "CU-NLP at SemEval-2016 task 8: AMR parsing using LSTM-based recurrent neural networks," in In Proceedings of the 10th InternationalWorkshop on Semantic Evaluation (SemEval-2016), San Diego, California, 2016. [DOI:10.18653/v1/S16-1185]
45. [45] Foland, William; Martin, James H., "Abstract meaning representation parsing using LSTM recurrent neural networks," in In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Vancouver, Canada, 2017. [DOI:10.18653/v1/P17-1043]
46. [46] Rao, Sudha; Vyas, Yogarshi; Daumé III, Hal; Resnik, Philip, "CLIP@UMD at SemEval-2016 Task 8: Parser for Abstract Meaning Representation using Learning to Search," in In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), San Diego, California, 2016. [DOI:10.18653/v1/S16-1184]
47. [47] Wang, Chuan; Xue, Nianwen; Pradhan, Sameer, "Boosting transition-based AMR parsing with refined actions and auxiliary analyzers," in In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), Beijing, China, 2015a. [DOI:10.3115/v1/P15-2141]
48. [48] Goodman, James; Vlachos, Andreas; Naradowsky, Jason, "UCL+Sheffield at SemEval-2016 Task 8: Imitation learning for AMR parsing with an alpha-bound," in In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), San Diego, California, 2016b. [DOI:10.18653/v1/S16-1180]
49. [49] Puzikov, Yevgeniy; Kawahara, Daisuke; Kurohashi, Sadao, "M2L at SemEval-2016 task 8: AMR parsing with neural networks," in In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), San Diego, California, 2016. [DOI:10.18653/v1/S16-1178]
50. [50] Wang, Chuan; Xue, Nianwen, "Getting the Most out of AMR Parsing," in In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017, Copenhagen, Denmark, 2017. [DOI:10.18653/v1/D17-1129]
51. [51] Nguyen, Khoa; Nguyen, Dang, "UIT-DANGNTCLNLP at SemEval-2017 Task 9: Building Scientific Concept Fixing Patterns for Improving CAMR," in In Proceedings of the 11th InternationalWorkshop on Semantic Evaluation (SemEval-2017), Vancouver, Canada, 2017. [DOI:10.18653/v1/S17-2156]
52. [52] Gruzitis, Normunds; Gosko, Didzis; Barzdins, Guntis, "RIGOTRIO at SemEval-2017 Task 9: Combining Machine Learning and Grammar Engineering for AMR Parsing and Generation.," in In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), Vancouver, Canada, 2017. [DOI:10.18653/v1/S17-2159]
53. [53] Wang, Chuan; Xue, Nianwen; Pradhan, Sameer, "A transition-based algorithm for amr parsing," in Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, 2015b. [DOI:10.3115/v1/N15-1040]
54. [54] Brandt, Lauritz; Grimm, David; Zhou, Mengfei; Versley, Yannick, "ICL-HD at SemEval-2016 Task 8: Meaning Representation Parsing - Augmenting AMR Parsing with a Preposition Semantic Role Labeling Neural Network," in In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), San Diego, California, 2016. [DOI:10.18653/v1/S16-1179]
55. [55] Goodman, James; Vlachos, Andreas; Naradowsky, Jason, "Noise reduction and targeted exploration in imitation learning for abstract meaning representation parsing," in Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Berlin, Germany, 2016a. [DOI:10.18653/v1/P16-1001]
56. [56] Ballesteros, Miguel; Al-Onaizan, Yaser, "AMR Parsing using Stack-LSTMs," in In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, Copenhagen, Denmark, 2017. [DOI:10.18653/v1/D17-1130]
57. [57] Damonte, Marco; Cohen, Shay B.; Satta, Giorgio, "An Incremental Parser for Abstract Meaning Representation," in In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, Valencia, Spain, 2017. [DOI:10.18653/v1/E17-1051]
58. [58] Peng, Xiaochang; Wang, Chuan; Gildea, Daniel; Xue, Nianwen, "Addressing the Data Sparsity Issue in Neural AMR Parsing," in In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, Valencia, Spain, 2017. [DOI:10.18653/v1/E17-1035]
59. [59] Groschwitz, Jonas; Lindemann, Matthias; Fowlie, Meaghan; Johnson, Mark; Koller, Alexander, "AMR dependency parsing with a typed semantic algebra," in The 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Melbourne, Australia, 2018. [DOI:10.18653/v1/P18-1170]
60. [60] Groschwitz, Jonas; Fowlie, Meaghan; Johnson, Mark; Koller, Alexander, "A constrained graph algebra for semantic parsing with AMRs," in The 12th International Conference on Computational Semantics (IWCS), 2017.
61. [61] Vilares, David; Gómez-Rodríguez, Carlos, "A Transition-Based Algorithm for Unrestricted AMR Parsing," in The 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), New Orleans, Louisiana, 2018. [DOI:10.18653/v1/N18-2023]
62. [62] Wang, Chuan; Li, Bin; Xue, Nianwen, "Transition-Based Chinese AMR Parsing," in The 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), New Orleans, Louisiana, 2018. [DOI:10.18653/v1/N18-2040]
63. [63] Guo, Zhijiang; Lu, Wei, "Better Transition-Based AMR Parsing with a Refined Search Space," in The 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, 2018. [DOI:10.18653/v1/D18-1198]
64. [64] Naseem, Tahira; Shah, Abhishek; Wan, Hui; Florian, Radu; Roukos, Salim; Ballesteros, Miguel, "Rewarding Smatch: Transition-Based AMR Parsing with Reinforcement Learning," in The 57th Annual Meeting of the Association for Computational Linguistics, Florence, Italy, 2019. [DOI:10.18653/v1/P19-1451]
65. [65] Welch, Charles; Kummerfeld, Jonathan K.; Feng, Song; Mihalcea, Rada, "World Knowledge for Abstract Meaning Representation Parsing," in The Eleventh International Conference on Language Resources and Evaluation (LREC 2018), Miyazaki, Japan, 2018.
66. [66] Gu, Min; Gu, Yanhui; Luo, Weilan; Xu, Guandong; Yang, Zhenglu; Zhou, Junsheng; Qu, Weiguang, "From text to graph: a general transition-based AMR parsing using neural network," Neural Computing and Applications, 2020. [DOI:10.1007/s00521-020-05378-5]
67. [67] Zhou, Jiawei; Naseem, Tahira; Astudillo, Ramón Fernandez; Florian, Radu, "AMR Parsing with Action-Pointer Transformer," in the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Online, 2021. [DOI:10.18653/v1/2021.naacl-main.443]
68. [68] Barzdins, Guntis; Gosko, Didzis, "RIGA at SemEval- 2016 Task 8: Impact of Smatch Extensions and Character-Level Neural Translation on AMR Parsing Accuracy," in In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), San Diego, California, 2016. [DOI:10.18653/v1/S16-1176]
69. [69] Konstas, Ioannis; Iyer, Srinivasan; Yatskar, Mark; Choi, Yejin; Zettlemoyer, Luke, "Neural AMR: Sequence-to-Sequence Models for Parsing and Generation," in In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, Vancouver, Canada, 2017. [DOI:10.18653/v1/P17-1014]
70. [70] Buys, Jan; Blunsom, Phil, "Robust Incremental Neural Semantic Graph Parsing," arXiv, p. 1215-1226, 2017. [DOI:10.18653/v1/P17-1112]
71. [71] Misra, Dipendra Kumar; Artzi, Yoav, "Neural shiftreduce ccg semantic parsing," in In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, Austin, Texas, 2016. [DOI:10.18653/v1/D16-1183]
72. [72] van Noord, Rik; Bos, Johan, "Dealing with Coreference in Neural Semantic Parsing," in In Proceedings of the 2nd Workshop on Semantic Deep Learning (SemDeep-2), 2017a.
73. [73] Zhang, Sheng; Ma, Xutai; Duh, Kevin; Van Durme, Benjamin, "AMR Parsing as Sequence-to-Graph Transduction," in The 57th Annual Meeting of the Association for Computational Linguistics, Florence, Italy, 2019. [DOI:10.18653/v1/P19-1009]
74. [74] Dozat, Timothy; Manning, Christopher D., "Deep Biaffine Attention for Neural Dependency Parsing," in arXiv:1611.01734, 2016.
75. [75] Bai, Xuefeng; Chen, Yulong; Zhang, Yue, "Graph Pre-training for AMR Parsing and Generation," arXiv:2203.07836, vol. 3, pp. 1-15, 2022. [DOI:10.18653/v1/2022.acl-long.415]
76. [76] Lewis, Mike; Liu, Yinhan; Goyal, Naman; Ghazvininejad, Marjan; Mohamed, Abdelrahman; Levy, Omer; Stoyanov, Veselin; Zettlemoyer, Luke, "BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension," in The 58th Annual Meeting of the Association for Computational Linguistics, Online, 2020. [DOI:10.18653/v1/2020.acl-main.703]
77. [77] Pust, Michael; Hermjakob, Ulf; Knight, Kevin; Marcu, Daniel; May, Jonathan, "Parsing English into Abstract Meaning Representation Using Syntax-Based Machine Translation," in In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, Lisbon, Portugal, 2015. [DOI:10.18653/v1/D15-1136]
78. [78] Lyu, Chunchuan; Titov, Ivan, "AMR Parsing as Graph Prediction with Latent Alignment," in In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Melbourne, Australia, 2018. [DOI:10.18653/v1/P18-1037]
79. [79] Gildea, Daniel; Jurafsky, Daniel, "Automatic Labeling of Semantic Roles," in In 38th Annual Meeting of the Association for Computational Linguistics, Hong Kong, 2000. [DOI:10.3115/1075218.1075283]
80. [80] V. Klimeš, "Analytical and Tectogrammatical Analysis of a Natural Language," Ph.D. thesis, Charles University, Prague, 2006a.
81. [81] V. Klimeš, "Transformation-based tectogrammatical analysis of czech," in In International Conference on Text, Speech and Dialogue, Berlin, Heidelberg, 2006b. [DOI:10.1007/11846406_17]
82. [82] V. Klimeš, "Transformation-based tectogrammatical dependency analysis of english," in In International Conference on Text, Speech and Dialogue, Berlin, Heidelberg, 2007.
83. [83] Bohnet, Bernd; Wanner, Leo; Mille, Simon; Burga, Alicia, "Broad coverage multilingual deep sentence generation with a stochastic multi-level realizer," in In Proceedings of the 23rd International Conference on Computational Linguistics, Beijing, China, 2010.
84. [84] Langkilde, Irene; Knight, Kevin, "Generation that exploits corpus-based statistical knowledge," in In Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics, Volume 1, Montreal, Quebec, Canada, 1998. [DOI:10.3115/980845.980963]
85. [85] Wong, Yuk Wah; Mooney, Raymond, "Generation by inverting a semantic parser that uses statistical machine translation," in Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Proceedings of the Main Conference, Rochester, New York, 2007. [DOI:10.3115/1220835.1220891]
86. [86] Belz, Anja; White, Michael; Espinosa, Dominic; Kow, Eric; Hogan, Deirdre; Stent, Amanda, "The first surface realisation shared task: Overview and evaluation results," in In Proceedings of the 13th European workshop on natural language generation, Nancy, France, 2011.
87. [87] I. Langkilde, "Forest-based statistical sentence Generation," in In proceedings of 1st Meeting of the North American Chapter of the Association for Computational Linguistics, 2000.
88. [88] Flanigan, Jeffrey; Dyer, Chris; Smith, Noah A.; Carbonell, Jaime, "Generation from abstract meaning representation using tree transducers," in In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, San Diego, California, 2016b. [DOI:10.18653/v1/N16-1087]
89. [89] Pelja Paul, N.; Revathy, P.; Sini, G.M.; Binu, R., "Automatic AMR Generation for Simple Sentences Using Dependency Parser," Procedia Technology, vol. 24, pp. 1528-1533, 2016. [DOI:10.1016/j.protcy.2016.05.119]
90. [90] Song, Linfeng; Peng, Xiaochang; Zhang, Yue; Wang, Zhiguo; Gildea, Daniel, "AMR-to-text Generation with Synchronous Node Replacement Grammar," in In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Vancouver, Canada, 2017. [DOI:10.18653/v1/P17-2002]
91. [91] Song, Linfeng; Zhang, Yue; Peng, Xiaochang; Wang, Zhiguo; Gildea, Daniel, "AMR-to-text generation as a Traveling Salesman Problem," in In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, Austin, Texas, 2016. [DOI:10.18653/v1/D16-1224]
92. [92] Pourdamghani, Nima; Knight, Kevin; Hermjakob, Ulf, "Generating english from abstract meaning representations," in In Proceedings of the 9th International Natural Language Generation conference, Edinburgh, UK, 2016. [DOI:10.18653/v1/W16-6603]
93. [93] Fan, Angela; Gardent, Claire, "Multilingual AMR-to-Text Generation," in The 2020 Conference on Empirical Methods in Natural Language Processing, Online, 2020. [DOI:10.18653/v1/2020.emnlp-main.231]
94. [94] Mille, Simon; Carlini, Roberto; Burga, Alicia; Wanner, Leo , "FORGe at SemEval-2017 Task 9: Deep sentence generation based on a sequence of graph transducers," in In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), Vancouver, Canada, 2017. [DOI:10.18653/v1/S17-2158]
95. [95] Lampouras, Gerasimos; Vlachos, Andreas, "Sheffield at SemEval-2017 Task 9: Transition-based language generation from AMR," in In Proceedings of the 11th InternationalWorkshop on Semantic Evaluation (SemEval-2017), Vancouver, Canada, 2017. [DOI:10.18653/v1/S17-2096]
96. [96] T. Schick, "Transition-Based Generation from Abstract Meaning Representations," Master's thesis, 2017.
97. [97] Jin, Lisa; Gildea, Daniel, "Generalized Shortest-Paths Encoders for AMR-to-Text Generation," in The 28th International Conference on Computational Linguistics, Barcelona, Spain (Online), 2020. [DOI:10.18653/v1/2020.coling-main.181]
98. [98] Ballesteros, Miguel; Bohnet, Bernd; Mille, Simon; Wanner, Leo, "Data-driven sentence generation with non-isomorphic trees," in Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, 2015. [DOI:10.3115/v1/N15-1042]
99. [99] May, Jonathan; Priyadarshi, Jay, "Semeval-2017 task 9: Abstract meaning representation parsing and generation," in In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), Vancouver, Canada, 2017. [DOI:10.18653/v1/S17-2090]
100. [100] Knight, Kevin; Badarau, Bianca; Baranescu, Laura; Bonial, Claire; Bardocz, Madalina; Griffitt, Kira; Hermjakob, Ulf; Marcu, Daniel; Palmer, Martha; O'Gorman, Tim; Schneider, Nathan, "Abstract Meaning Representation (AMR) Annotation Release 3.0," Linguistic Data Consortium, Philadelphia, 2020.
101. [101] Zettlemoyer, Luke S.; Collins, Michael, "Learning to Map Sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars," in In UAI '05, Proceedings of the 21st Conference in Uncertainty in Artificial Intelligence, 2005.
102. [102] Papineni, Kishore; Roukos, Salim; Ward, Todd; Zhu, Wei-Jing, "Bleu: a Method for Automatic Evaluation of Machine Translation," in The 40th Annual Meeting of the Association for Computational Linguistics, Philadelphia, Pennsylvania, USA, 2002. [DOI:10.3115/1073083.1073135]
103. [103] Allen, James F.; Swift, Mary; Beaumont, Will De, "Deep semantic analysis of text," in In Proceedings of the 2008 Conference on Semantics in Text Processing, 2008. [DOI:10.3115/1626481.1626508]
104. [104] Dridan, Rebecca; Oepen, Stephan, "Parser Evaluation using Elementary Dependency Matching," in In Proceedings of the 12th International Conference on Parsing Technologies, Dublin, Ireland, 2011.
105. [105] Opitz, Juri; Parcalabescu, Letitia; Frank, Anette, "AMR Similarity Metrics from Principles," Transactions of the Association for Computational Linguistics, vol. 8, p. 522-538, 2020. [DOI:10.1162/tacl_a_00329]
106. [106] van Noord, Rik; Bos, Johan, "Neural semantic parsing by character-based translation: Experiments with abstract meaning representations," arXiv:1705.09980, 2017b.
107. [107] Song, Li; Dai, Yuling; Liu, Yihuan; Li, Bin; Qu, Weiguang, "Construct a Sense-Frame Aligned Predicate Lexicon for Chinese AMR Corpus," in The 12th Language Resources and Evaluation Conference, Marseille, France, 2020.
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
