paper-with-me

홈 › Papers

Nomen Omen. Enhancing the Latin Morphological Analyser Lemlat with an Onomasticon

2016-08-01 · WS 2016 8 · Marco Budassi, Marco Passarotti
📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Tasks

Morphological AnalysisMorphological InflectionNamed Entity Recognition (NER)

Similar Papers 제목 키워드 기반

AnIta: a powerful morphological analyser for Italian

2012-05-01 · LREC 2012 5 · Fabio Tamburini, Mel, Matias ri

In this paper we present AnIta, a powerful morphological analyser for Italian implemented within the framework of finite-state-automata models. It is provided by a large lexicon containing more than 110,000 lemmas that e…

ManagementPOS

A Finite-State Morphological Analyser for Evenki

2020-05-01 · LREC 2020 5 · Anna Zueva, Anastasia Kuznetsova, Francis Tyers

It has been widely admitted that morphological analysis is an important step in automated text processing for morphologically rich languages. Evenki is a language with rich morphology, therefore a morphological analyser …

Morphological Analysisvalid

A finite-state morphological analyser for Paraguayan Guaraní

2021-06-01 · NAACL (AmericasNLP) 2021 6 · Anastasia Kuznetsova, Francis Tyers

This article describes the development of morphological analyser for Paraguayan Guaraní, agglutinative indigenous language spoken by nearly 6 million people in South America. The implementation of our analyser uses HFST …

Neural disambiguation of lemma and part of speech in morphologically rich languages

2020-07-12 · LREC 2020 5 · José María Hoya Quecedo, Maximilian W. Koppatz, Giacomo Furlan, Roman Yangarber

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 c…

LEMMAPOS

How Suitable Are Subword Segmentation Strategies for Translating Non-Concatenative Morphology?

2021-09-02 · Findings (EMNLP) 2021 11 · Chantal Amrhein, Rico Sennrich

Data-driven subword segmentation has become the default strategy for open-vocabulary machine translation and other NLP tasks, but may not be sufficiently generic for optimal learning of non-concatenative morphology. We d…

Machine TranslationSegmentationTranslation