Unsupervised Morphological Paradigm Completion
Huiming Jin, Liwei Cai, Yihui Peng, Chen Xia, Arya McCarthy, Katharina Kann
摘要
We propose the task of unsupervised morphological paradigm completion. Given only raw text and a lemma list, the task consists of generating the morphological paradigms, i.e., all inflected forms, of the lemmas. From a natural language processing (NLP) perspective, this is a challenging unsupervised task, and high-performing systems have the potential to improve tools for low-resource languages or to assist linguistic annotators. From a cognitive science perspective, this can shed light on how children acquire morphological knowledge. We further introduce a system for the task, which generates morphological paradigms via the following steps: (i) EDIT TREE retrieval, (ii) additional lemma retrieval, (iii) paradigm size discovery, and (iv) inflection generation. We perform an evaluation on 14 typologically diverse languages. Our system outperforms trivial baselines with ease and, for some languages, even obtains a higher accuracy than minimally supervised systems. 1
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- IGT2P: From Interlinear Glossed Texts to ParadigmsSarah R. Moeller, Ling Liu, Changbing Yang, Katharina Kann 等EMNLP 2020 · 被引用 13 次
- The Zeno's Paradox of 'Low-Resource' LanguagesHellina Hailu Nigatu, Atnafu Lambebo Tonja, Benjamin Rosman, Thamar Solorio 等EMNLP 2024 · 被引用 10 次
- Counting the Bugs in ChatGPT's Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language ModelLeonie Weissweiler, Valentin Hofmann, Anjali Kantharuban, Anna Cai 等EMNLP 2023 · 被引用 10 次
- CaMEL: Case Marker Extraction without LabelsLeonie Weissweiler, Valentin Hofmann, Masoud Jalili Sabet, Hinrich SchützeACL 2022 · 被引用 3 次
- The Paradigm Discovery ProblemAlexander Erdmann, Micha Elsner, Shijie Wu, Ryan Cotterell 等ACL 2020 · 被引用 1 次
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