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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 141150 of 351 papers

TitleStatusHype
Improving Lemmatization of Non-Standard Languages with Joint LearningCode0
Few-Shot and Zero-Shot Learning for Historical Text Normalization0
Universal Lemmatizer: A Sequence to Sequence Model for Lemmatizing Universal Dependencies Treebanks0
Data-Driven Morphological Analysis for Uralic Languages0
Joint Learning of POS and Dependencies for Multilingual Universal Dependency ParsingCode0
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
UZH@SMM4H: System Descriptions0
LemmaTag: Jointly Tagging and Lemmatizing for Morphologically Rich Languages with BRNNsCode0
Attention-free encoder decoder for morphological processing0
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