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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 5160 of 351 papers

TitleStatusHype
Enhancing Sequence-to-Sequence Neural Lemmatization with External ResourcesCode0
Transformers on Multilingual Clause-Level MorphologyCode0
Cross-lingual Named Entity Corpus for Slavic LanguagesCode0
Training Data Augmentation for Context-Sensitive Neural Lemmatization Using Inflection Tables and Raw TextCode0
CMU-01 at the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in MorphologyCode0
Cross-Lingual Lemmatization and Morphology Tagging with Two-Stage Multilingual BERT Fine-TuningCode0
DBTagger: Multi-Task Learning for Keyword Mapping in NLIDBs Using Bi-Directional Recurrent Neural NetworksCode0
SoMeWeTa: A Part-of-Speech Tagger for German Social Media and Web TextsCode0
Sudachi: a Japanese Tokenizer for BusinessCode0
From Text to Lexicon: Bridging the Gap between Word Embeddings and Lexical ResourcesCode0
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