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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

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Showing 301–325 of 351 papers

TitleStatusHype
The Floating Arabic Dictionary: An Automatic Method for Updating a Lexical Database through the Detection and Lemmatization of Unknown Words—0
The goo300k corpus of historical Slovene—0
Transformers on Multilingual Clause-Level MorphologyCode0
Towards JointUD: Part-of-speech Tagging and Lemmatization using Recurrent Neural NetworksCode0
SoMaJo: State-of-the-art tokenization for German web and social media textsCode0
LemmaTag: Jointly Tagging and Lemmatizing for Morphologically-Rich Languages with BRNNsCode0
LemmaTag: Jointly Tagging and Lemmatizing for Morphologically Rich Languages with BRNNsCode0
SoMeWeTa: A Part-of-Speech Tagger for German Social Media and Web TextsCode0
The Role of Interpretable Patterns in Deep Learning for MorphologyCode0
Analyzing Pre-processing Settings for Urdu Single-document Extractive SummarizationCode0
DBTagger: Multi-Task Learning for Keyword Mapping in NLIDBs Using Bi-Directional Recurrent Neural NetworksCode0
From Text to Lexicon: Bridging the Gap between Word Embeddings and Lexical ResourcesCode0
Beyond Stemming and Lemmatization: Ultra-stemming to Improve Automatic Text SummarizationCode0
Unsupervised Compound Splitting With Distributional Semantics Rivals Supervised MethodsCode0
Training Data Augmentation for Context-Sensitive Neural Lemmatization Using Inflection Tables and Raw TextCode0
Grammatical gender associations outweigh topical gender bias in crosslinguistic word embeddingsCode0
Training Data Augmentation for Context-Sensitive Neural Lemmatizer Using Inflection Tables and Raw TextCode0
Neural Transition-based String Transduction for Limited-Resource Setting in MorphologyCode0
Stylistic Fingerprints, POS-tags and Inflected Languages: A Case Study in PolishCode0
Heidelberg-Boston @ SIGTYP 2024 Shared Task: Enhancing Low-Resource Language Analysis With Character-Aware Hierarchical TransformersCode0
Lexicon and Rule-based Word Lemmatization Approach for the Somali LanguageCode0
NLP-Cube: End-to-End Raw Text Processing With Neural NetworksCode0
Sudachi: a Japanese Tokenizer for BusinessCode0
Evaluating Shortest Edit Script Methods for Contextual LemmatizationCode0
Enhancing Sequence-to-Sequence Neural Lemmatization with External ResourcesCode0
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