@inproceedings{batsuren-etal-2021-morphynet,
title = "{M}orphy{N}et: a Large Multilingual Database of Derivational and Inflectional Morphology",
author = "Batsuren, Khuyagbaatar and
Bella, G{\'a}bor and
Giunchiglia, Fausto",
editor = "Nicolai, Garrett and
Gorman, Kyle and
Cotterell, Ryan",
booktitle = "Proceedings of the 18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.sigmorphon-1.5",
doi = "10.18653/v1/2021.sigmorphon-1.5",
pages = "39--48",
abstract = "Large-scale morphological databases provide essential input to a wide range of NLP applications. Inflectional data is of particular importance for morphologically rich (agglutinative and highly inflecting) languages, and derivations can be used, e.g. to infer the semantics of out-of-vocabulary words. Extending the scope of state-of-the-art multilingual morphological databases, we announce the release of MorphyNet, a high-quality resource with 15 languages, 519k derivational and 10.1M inflectional entries, and a rich set of morphological features. MorphyNet was extracted from Wiktionary using both hand-crafted and automated methods, and was manually evaluated to be of a precision higher than 98{\%}. Both the resource generation logic and the resulting database are made freely available and are reusable as stand-alone tools or in combination with existing resources.",
}
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<abstract>Large-scale morphological databases provide essential input to a wide range of NLP applications. Inflectional data is of particular importance for morphologically rich (agglutinative and highly inflecting) languages, and derivations can be used, e.g. to infer the semantics of out-of-vocabulary words. Extending the scope of state-of-the-art multilingual morphological databases, we announce the release of MorphyNet, a high-quality resource with 15 languages, 519k derivational and 10.1M inflectional entries, and a rich set of morphological features. MorphyNet was extracted from Wiktionary using both hand-crafted and automated methods, and was manually evaluated to be of a precision higher than 98%. Both the resource generation logic and the resulting database are made freely available and are reusable as stand-alone tools or in combination with existing resources.</abstract>
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%0 Conference Proceedings
%T MorphyNet: a Large Multilingual Database of Derivational and Inflectional Morphology
%A Batsuren, Khuyagbaatar
%A Bella, Gábor
%A Giunchiglia, Fausto
%Y Nicolai, Garrett
%Y Gorman, Kyle
%Y Cotterell, Ryan
%S Proceedings of the 18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F batsuren-etal-2021-morphynet
%X Large-scale morphological databases provide essential input to a wide range of NLP applications. Inflectional data is of particular importance for morphologically rich (agglutinative and highly inflecting) languages, and derivations can be used, e.g. to infer the semantics of out-of-vocabulary words. Extending the scope of state-of-the-art multilingual morphological databases, we announce the release of MorphyNet, a high-quality resource with 15 languages, 519k derivational and 10.1M inflectional entries, and a rich set of morphological features. MorphyNet was extracted from Wiktionary using both hand-crafted and automated methods, and was manually evaluated to be of a precision higher than 98%. Both the resource generation logic and the resulting database are made freely available and are reusable as stand-alone tools or in combination with existing resources.
%R 10.18653/v1/2021.sigmorphon-1.5
%U https://aclanthology.org/2021.sigmorphon-1.5
%U https://doi.org/10.18653/v1/2021.sigmorphon-1.5
%P 39-48
Markdown (Informal)
[MorphyNet: a Large Multilingual Database of Derivational and Inflectional Morphology](https://aclanthology.org/2021.sigmorphon-1.5) (Batsuren et al., SIGMORPHON 2021)
ACL