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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 110 of 351 papers

TitleStatusHype
NeoN: A Tool for Automated Detection, Linguistic and LLM-Driven Analysis of Neologisms in Polish0
ParsiPy: NLP Toolkit for Historical Persian Texts in PythonCode1
Breaking the Fake News Barrier: Deep Learning Approaches in Bangla Language0
Context Aware Lemmatization and Morphological Tagging Method in Turkish0
GliLem: Leveraging GliNER for Contextualized Lemmatization in Estonian0
SinaTools: Open Source Toolkit for Arabic Natural Language Processing0
A State-of-the-Art Morphosyntactic Parser and Lemmatizer for Ancient GreekCode1
A Comparative Study of Hybrid Models in Health Misinformation Text Classification0
One Model is All You Need: ByT5-Sanskrit, a Unified Model for Sanskrit NLP TasksCode1
ACE-2005-PT: Corpus for Event Extraction in Portuguese0
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