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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 151160 of 351 papers

TitleStatusHype
NLP-Cube: End-to-End Raw Text Processing With Neural NetworksCode0
Turku Neural Parser Pipeline: An End-to-End System for the CoNLL 2018 Shared Task0
LemmaTag: Jointly Tagging and Lemmatizing for Morphologically Rich Languages with BRNNsCode0
Building a Lemmatizer and a Spell-checker for Sorani Kurdish0
Towards JointUD: Part-of-speech Tagging and Lemmatization using Recurrent Neural NetworksCode0
Imitation Learning for Neural Morphological String TransductionCode0
LemmaTag: Jointly Tagging and Lemmatizing for Morphologically-Rich Languages with BRNNsCode0
Neural Transition-based String Transduction for Limited-Resource Setting in MorphologyCode0
Local String Transduction as Sequence Labeling0
From Text to Lexicon: Bridging the Gap between Word Embeddings and Lexical ResourcesCode0
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