Papers with morphological paradigms

4 papers
A Computational Model of Latvian Morphology (2024.lrec-main)

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Challenge: a computational model of Latvian morphology provides a formal structure for Latvian word form inflection . the model explicitly enumerates and handles the many exceptions to the general Latvian inflation principles .
Approach: They propose a computational model of Latvian morphology that provides a formal structure for Latvian word form inflection.
Outcome: The proposed model provides a good coverage for modern Latvian literary language and potential to extend to Latgalian language.
K-UniMorph: Korean Universal Morphology and its Feature Schema (2023.findings-acl)

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Challenge: Previously, the Korean language has been underrepresented in the field of morphological paradigms amongst hundreds of diverse world languages.
Approach: They propose a new Universal Morphology dataset for Korean that preserves its distinct characteristics.
Outcome: The proposed dataset extracts inflected Korean verb forms from the largest annotated corpus for Korean.
IGT2P: From Interlinear Glossed Texts to Paradigms (2020.emnlp-main)

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Challenge: Existing systems for learning morphology have limited their use to languages with publicly available structured data, such as online dictionaries like Wiktionary.
Approach: They propose a task that generates entire morphological paradigms from IGT input and a language expert cleaning noisy IGT data.
Outcome: The proposed task speeds up the process and generates entire morphological paradigm tables from IGT input.
Unsupervised Morphological Paradigm Completion (2020.acl-main)

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Challenge: a task of generating morphological paradigms is a challenging unsupervised task for natural language processing systems . acuidados y acciones del idioma es a problem in linguistic annotators.
Approach: They propose a task of unsupervised morphological paradigm completion using raw text and a lemma list.
Outcome: The proposed system outperforms trivial baselines on 14 typologically diverse languages with ease and higher accuracy than minimally supervised systems.

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