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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 131140 of 351 papers

TitleStatusHype
Development of email classifier in Brazilian Portuguese using feature selection for automatic response0
Learning Morphosyntactic Analyzers from the Bible via Iterative Annotation Projection across 26 Languages0
Training Data Augmentation for Context-Sensitive Neural Lemmatizer Using Inflection Tables and Raw TextCode0
USF at SemEval-2019 Task 6: Offensive Language Detection Using LSTM With Word Embeddings0
Revisiting NMT for Normalization of Early English LettersCode0
Morphological parsing of low‑resource languagesCode0
Producing Corpora of Medieval and Premodern Occitan0
A Simple Joint Model for Improved Contextual Neural Lemmatization0
Training Data Augmentation for Context-Sensitive Neural Lemmatization Using Inflection Tables and Raw TextCode0
Multilevel Text Normalization with Sequence-to-Sequence Networks and Multisource Learning0
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