Findings of the SIGMORPHON 2021 Shared Task on Unsupervised Morphological Paradigm Clustering

Proceedings of the 18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology Pub Date : 1900-01-01 DOI:10.18653/v1/2021.sigmorphon-1.8

Adam Wiemerslage, Arya D. McCarthy, Alexander Erdmann, Garrett Nicolai, Manex Agirrezabal, Miikka Silfverberg, Mans Hulden, Katharina Kann

引用次数: 5

Abstract

We describe the second SIGMORPHON shared task on unsupervised morphology: the goal of the SIGMORPHON 2021 Shared Task on Unsupervised Morphological Paradigm Clustering is to cluster word types from a raw text corpus into paradigms. To this end, we release corpora for 5 development and 9 test languages, as well as gold partial paradigms for evaluation. We receive 14 submissions from 4 teams that follow different strategies, and the best performing system is based on adaptor grammars. Results vary significantly across languages. However, all systems are outperformed by a supervised lemmatizer, implying that there is still room for improvement.

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SIGMORPHON 2021共享任务在无监督形态范式聚类中的发现

我们描述了关于无监督形态学的第二个SIGMORPHON共享任务:关于无监督形态学范式聚类的SIGMORPHON 2021共享任务的目标是将原始文本语料库中的词类型聚类到范式中。为此，我们发布了5种开发语言和9种测试语言的语料库，以及用于评估的黄金部分范例。我们收到了来自4个团队的14份提交，他们遵循不同的策略，表现最好的系统是基于适配器语法的。不同语言的结果差异很大。然而，所有系统的性能都优于有监督的归纳器，这意味着仍有改进的空间。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the 18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology

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