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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 2130 of 351 papers

TitleStatusHype
Grammatical gender associations outweigh topical gender bias in crosslinguistic word embeddingsCode0
Improving Lemmatization of Non-Standard Languages with Joint LearningCode0
Evaluating Shortest Edit Script Methods for Contextual LemmatizationCode0
Transformers on Multilingual Clause-Level MorphologyCode0
An Automated Text Categorization Framework based on Hyperparameter OptimizationCode0
Enhancing Sequence-to-Sequence Neural Lemmatization with External ResourcesCode0
From Text to Lexicon: Bridging the Gap between Word Embeddings and Lexical ResourcesCode0
Heidelberg-Boston @ SIGTYP 2024 Shared Task: Enhancing Low-Resource Language Analysis With Character-Aware Hierarchical TransformersCode0
Integrated Sequence Tagging for Medieval Latin Using Deep Representation LearningCode0
Training Data Augmentation for Context-Sensitive Neural Lemmatization Using Inflection Tables and Raw TextCode0
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