Abstract
Treebank selection for parsing evaluation and the spurious effects that might arise from a biased choice have not been explored in detail. This paper studies how evaluating on a single subset of treebanks can lead to weak conclusions. First, we take a few contrasting parsers, and run them on subsets of treebanks proposed in previous work, whose use was justified (or not) on criteria such as typology or data scarcity. Second, we run a large-scale version of this experiment, create vast amounts of random subsets of treebanks, and compare on them many parsers whose scores are available. The results show substantial variability across subsets and that although establishing guidelines for good treebank selection is hard, some inadequate strategies can be easily avoided.- Anthology ID:
- 2022.coling-1.475
- Volume:
- Proceedings of the 29th International Conference on Computational Linguistics
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 5345–5359
- Language:
- URL:
- https://aclanthology.org/2022.coling-1.475
- DOI:
- Bibkey:
- Cite (ACL):
- Iago Alonso-Alonso, David Vilares, and Carlos Gómez-Rodríguez. 2022. The Fragility of Multi-Treebank Parsing Evaluation. In Proceedings of the 29th International Conference on Computational Linguistics, pages 5345–5359, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
- Cite (Informal):
- The Fragility of Multi-Treebank Parsing Evaluation (Alonso-Alonso et al., COLING 2022)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.coling-1.475.pdf
- Code
- minionattack/fragility_coling_2022
Export citation
@inproceedings{alonso-alonso-etal-2022-fragility, title = "The Fragility of Multi-Treebank Parsing Evaluation", author = "Alonso-Alonso, Iago and Vilares, David and G{\'o}mez-Rodr{\'\i}guez, Carlos", editor = "Calzolari, Nicoletta and Huang, Chu-Ren and Kim, Hansaem and Pustejovsky, James and Wanner, Leo and Choi, Key-Sun and Ryu, Pum-Mo and Chen, Hsin-Hsi and Donatelli, Lucia and Ji, Heng and Kurohashi, Sadao and Paggio, Patrizia and Xue, Nianwen and Kim, Seokhwan and Hahm, Younggyun and He, Zhong and Lee, Tony Kyungil and Santus, Enrico and Bond, Francis and Na, Seung-Hoon", booktitle = "Proceedings of the 29th International Conference on Computational Linguistics", month = oct, year = "2022", address = "Gyeongju, Republic of Korea", publisher = "International Committee on Computational Linguistics", url = "https://aclanthology.org/2022.coling-1.475", pages = "5345--5359", abstract = "Treebank selection for parsing evaluation and the spurious effects that might arise from a biased choice have not been explored in detail. This paper studies how evaluating on a single subset of treebanks can lead to weak conclusions. First, we take a few contrasting parsers, and run them on subsets of treebanks proposed in previous work, whose use was justified (or not) on criteria such as typology or data scarcity. Second, we run a large-scale version of this experiment, create vast amounts of random subsets of treebanks, and compare on them many parsers whose scores are available. The results show substantial variability across subsets and that although establishing guidelines for good treebank selection is hard, some inadequate strategies can be easily avoided.", }
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%0 Conference Proceedings %T The Fragility of Multi-Treebank Parsing Evaluation %A Alonso-Alonso, Iago %A Vilares, David %A Gómez-Rodríguez, Carlos %Y Calzolari, Nicoletta %Y Huang, Chu-Ren %Y Kim, Hansaem %Y Pustejovsky, James %Y Wanner, Leo %Y Choi, Key-Sun %Y Ryu, Pum-Mo %Y Chen, Hsin-Hsi %Y Donatelli, Lucia %Y Ji, Heng %Y Kurohashi, Sadao %Y Paggio, Patrizia %Y Xue, Nianwen %Y Kim, Seokhwan %Y Hahm, Younggyun %Y He, Zhong %Y Lee, Tony Kyungil %Y Santus, Enrico %Y Bond, Francis %Y Na, Seung-Hoon %S Proceedings of the 29th International Conference on Computational Linguistics %D 2022 %8 October %I International Committee on Computational Linguistics %C Gyeongju, Republic of Korea %F alonso-alonso-etal-2022-fragility %X Treebank selection for parsing evaluation and the spurious effects that might arise from a biased choice have not been explored in detail. This paper studies how evaluating on a single subset of treebanks can lead to weak conclusions. First, we take a few contrasting parsers, and run them on subsets of treebanks proposed in previous work, whose use was justified (or not) on criteria such as typology or data scarcity. Second, we run a large-scale version of this experiment, create vast amounts of random subsets of treebanks, and compare on them many parsers whose scores are available. The results show substantial variability across subsets and that although establishing guidelines for good treebank selection is hard, some inadequate strategies can be easily avoided. %U https://aclanthology.org/2022.coling-1.475 %P 5345-5359
Markdown (Informal)
[The Fragility of Multi-Treebank Parsing Evaluation](https://aclanthology.org/2022.coling-1.475) (Alonso-Alonso et al., COLING 2022)
- The Fragility of Multi-Treebank Parsing Evaluation (Alonso-Alonso et al., COLING 2022)
ACL
- Iago Alonso-Alonso, David Vilares, and Carlos Gómez-Rodríguez. 2022. The Fragility of Multi-Treebank Parsing Evaluation. In Proceedings of the 29th International Conference on Computational Linguistics, pages 5345–5359, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.