Machine Learning and Deep Neural Network-Based Lemmatization and Morphosyntactic Tagging for Serbian
Објеката
- Тип
- Рад у зборнику
- Верзија рада
- објављена
- Језик
- енглески
- Креатор
- Ranka Stanković, Branislava Šandrih, Cvetana Krstev, Miloš Utvić, Mihailo Škorić
- Извор
- Proceedings of the 12th Language Resources and Evaluation Conference, May Year: 2020, Marseille, France
- Издавач
- European Language Resources Association
- Датум издавања
- 2020
- Сажетак
- The training of new tagger models for Serbian is primarily motivated by the enhancement of the existing tagset with the grammatical category of a gender. The harmonization of resources that were manually annotated within different projects over a long period of time was an important task, enabled by the development of tools that support partial automation. The supporting tools take into account different taggers and tagsets. This paper focuses on TreeTagger and spaCy taggers, and the annotation schema alignment between Serbian morphological dictionaries, MULTEXT-East and Universal Part-of-Speech tagset. The trained models will be used to publish the new version of the Corpus of Contemporary Serbian as well as the Serbian literary corpus. The performance of developed taggers were compared and the impact of training set size was investigated, which resulted in around 98% PoS-tagging precision per token for both new models. The sr_basic annotated dataset will also be published.
- почетак странице
- 3954
- крај странице
- 3962
- Subject
- Part-of-Speech tagging, lemmatization, corpus, evaluation, Serbian, morphological dictionary
- Шира категорија рада
- М30
- Ужа категорија рада
- М33
- Права
- Отворени приступ
- Лиценца
- All rights reserved
- Формат
- Медија
2020.lrec-1.487.pdf
Ranka Stanković, Branislava Šandrih, Cvetana Krstev, Miloš Utvić, Mihailo Škorić. "Machine Learning and Deep Neural Network-Based Lemmatization and Morphosyntactic Tagging for Serbian" in Proceedings of the 12th Language Resources and Evaluation Conference, May Year: 2020, Marseille, France, European Language Resources Association (2020)
This item was submitted on 25. март 2021. by [anonymous user] using the form “Рад у зборнику радова” on the site “Радови”: http://drug.rgf.bg.ac.rs/s/repo
Click here to view the collected data.