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The SIGMORPHON 2022 Shared Task on Morpheme Segmentation

2022-06-15NAACL (SIGMORPHON) 2022Code Available1· sign in to hype

Khuyagbaatar Batsuren, Gábor Bella, Aryaman Arora, Viktor Martinović, Kyle Gorman, Zdeněk Žabokrtský, Amarsanaa Ganbold, Šárka Dohnalová, Magda Ševčíková, Kateřina Pelegrinová, Fausto Giunchiglia, Ryan Cotterell, Ekaterina Vylomova

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Abstract

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.

Tasks

Benchmark Results

DatasetModelMetricClaimedVerifiedStatus
UniMorph 4.0Morfessor2macro avg (subtask 1)25.57Unverified
UniMorph 4.0ULMmacro avg (subtask 1)20.61Unverified
UniMorph 4.0WordPiecemacro avg (subtask 1)15.89Unverified

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