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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 4150 of 351 papers

TitleStatusHype
LatinCy: Synthetic Trained Pipelines for Latin NLP0
BRENT: Bidirectional Retrieval Enhanced Norwegian TransformerCode0
Exploring the Use of Foundation Models for Named Entity Recognition and Lemmatization Tasks in Slavic Languages0
On the Role of Morphological Information for Contextual Lemmatization0
Automated Identification of Disaster News For Crisis Management Using Machine Learning0
H2-Golden-Retriever: Methodology and Tool for an Evidence-Based Hydrogen Research Grantsmanship0
Transformers on Multilingual Clause-Level MorphologyCode0
Development of a rule-based lemmatization algorithm through Finite State Machine for Uzbek language0
Arabic Word-level Readability Visualization for Assisted Text Simplification0
Social Media Personal Event Notifier Using NLP and Machine Learning0
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