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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 1120 of 351 papers

TitleStatusHype
Advancing Hungarian Text Processing with HuSpaCy: Efficient and Accurate NLP PipelinesCode1
ParsiPy: NLP Toolkit for Historical Persian Texts in PythonCode1
Stanza: A Python Natural Language Processing Toolkit for Many Human LanguagesCode1
A State-of-the-Art Morphosyntactic Parser and Lemmatizer for Ancient GreekCode1
One Model is All You Need: ByT5-Sanskrit, a Unified Model for Sanskrit NLP TasksCode1
Hybrid lemmatization in HuSpaCyCode1
ELIT: Emory Language and Information ToolkitCode1
Exploring Large Language Models for Classical PhilologyCode1
Opera Graeca Adnotata: Building a 34M+ Token Multilayer Corpus for Ancient GreekCode1
AI-KU: Using Co-Occurrence Modeling for Semantic Similarity0
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