The SIGMORPHON 2022 shared task on morpheme segmentation challenged systems to decompose a word into a sequence of morphemes and covered most types of morphology: compounds, derivations, and inflections. Subtask 1, word-level morpheme segmentation, covered 5 million words in 9 languages (Czech, English, Spanish, Hungarian, French, Italian, Russian, Latin, Mongolian) and received 13 system submissions from 7 teams and the best system averaged 97.29% F1 score across all languages, ranging English (93.84%) to Latin (99.38%). Subtask 2, sentence-level morpheme segmentation, covered 18,735 sentences in 3 languages (Czech, English, Mongolian), received 10 system submissions from 3 teams, and the best systems outperformed all three state-of-the-art subword tokenization methods (BPE, ULM, Morfessor2) by 30.71% absolute. To facilitate error analysis and support any type of future studies, we released all system predictions, the evaluation script, and all gold standard datasets.

该研究介绍了SIGMORPHON 2022 共享任务关于形态素分割，试图将单词分解为一系列形态素，并覆盖了大部分类型的形态学。结果表明，该任务的提交结果对于单词级别和句子级别的形态素分割与现有的3种子单词分割方法相比有显著提高，为错误分析和未来的研究提供了有用的数据。

SIGMORPHON 2022 共享任务：形态素切分