Neural Disambiguation of Lemma and Part of Speech in Morphologically Rich Languages
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10427006" target="_blank" >RIV/00216208:11320/20:10427006 - isvavai.cz</a>
Result on the web
<a href="https://www.aclweb.org/anthology/2020.lrec-1.439" target="_blank" >https://www.aclweb.org/anthology/2020.lrec-1.439</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Neural Disambiguation of Lemma and Part of Speech in Morphologically Rich Languages
Original language description
We consider the problem of disambiguating the lemma and part of speech of ambiguous words in morphologically rich languages. We propose a method for disambiguating ambiguous words in context, using a large un-annotated corpus of text, and a morphological analyser—with no manual disambiguation or data annotation. We assume that the morphological analyser produces multiple analyses for ambiguous words. The idea is to train recurrent neural networks on the output that the morphological analyser produces for unambiguous words. We present performance on POS and lemma disambiguation that reaches or surpasses the state of the art—including supervised models—using no manually annotated data. We evaluate the method on several morphologically rich languages.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů