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Lemmatization

Lemmatization is a process of determining a base or dictionary form (lemma) for a given surface form. Especially for languages with rich morphology it is important to be able to normalize words into their base forms to better support for example search engines and linguistic studies. Main difficulties in Lemmatization arise from encountering previously unseen words during inference time as well as disambiguating ambiguous surface forms which can be inflected variants of several different base forms depending on the context.

Source: Universal Lemmatizer: A Sequence to Sequence Model for Lemmatizing Universal Dependencies Treebanks

Papers

Showing 101110 of 351 papers

TitleStatusHype
Machine Learning and Deep Neural Network-Based Lemmatization and Morphosyntactic Tagging for Serbian0
A Gradient Boosting-Seq2Seq System for Latin POS Tagging and Lemmatization0
JHUBC's Submission to LT4HALA EvaLatin 20200
Overview of the EvaLatin 2020 Evaluation Campaign0
Voting for POS tagging of Latin texts: Using the flair of FLAIR to better Ensemble Classifiers by Example of Latin0
Lemmatization and POS-tagging process by using joint learning approach. Experimental results on Classical Armenian, Old Georgian, and Syriac0
A Resource for Studying Chatino Verbal Morphology0
Stanza: A Python Natural Language Processing Toolkit for Many Human LanguagesCode1
Morphological Tagging and Lemmatization of Albanian: A Manually Annotated Corpus and Neural ModelsCode0
\'UFAL MRPipe at MRP 2019: UDPipe Goes Semantic in the Meaning Representation Parsing Shared TaskCode0
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