natural-language-processing-3

Morphological Disambiguation

3260 papers • 126 benchmarks • 313 datasets

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Benchmarks

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Datasets

NEMO-Corpus

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Most implemented papers

A Morphology-Aware Network for Morphological Disambiguation

Eray Yildiz, C. Tirkaz, H. B. Sahin, M. Eren, O. O. Sonmez•Thu Feb 11 2016

This work proposes a system that uses deep learning techniques for morphological disambiguation in Turkish and presents results for French and German to show that the proposed architecture achieves high accuracy with no language-specific feature engineering or additional resource.

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Improving Named Entity Recognition by Jointly Learning to Disambiguate Morphological Tags

Onur Güngör, Suzan Üsküdarli, Tunga Güngör•Mon Jul 16 2018

This work proposes a model which alleviates the need for such disambiguators by jointly learning NER and MD taggers in languages for which one can provide a list of candidate morphological analyses, independent of the morphological annotation schemes, which differ among languages.

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A Little Pretraining Goes a Long Way: A Case Study on Dependency Parsing Task for Low-resource Morphologically Rich Languages

Pawan Goyal, Amrith Krishna, Ashim Gupta, Jivnesh Sandhan, L. Behera•Thu Feb 11 2021

This work proposes simple auxiliary tasks for pretraining for dependency parsing for morphological rich languages (MRLs) in a low-resource setting to address the challenges to get morphological information for MRLs.

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