The Fragility of Multi-Treebank Parsing Evaluation

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The Fragility of Multi-Treebank Parsing EvaluationData
2022-10Cita bibliográfica
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.
Resumo
[Absctract]: 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.
Palabras chave
Multi-Treebank Parsing Evaluation
Treebank Selection Bias
Evaluation Methodology
Parsing Performance Variability
Treebank Selection Bias
Evaluation Methodology
Parsing Performance Variability
Descrición
Held in Gyeongju, Republic of Korea. October 12-17, 2022
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Atribución 3.0 España