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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 151–200 of 351 papers

TitleStatusHype
Leveraging Inflection Tables for Stemming and Lemmatization.—0
Lexical Categories for Improved Parsing of Web Data—0
Lexical Correction of Polish Twitter Political Data—0
Lexicon-assisted tagging and lemmatization in Latin: A comparison of six taggers and two lemmatization methods—0
Linguistic Analysis Processing Line for Bulgarian—0
Linguistic change and historical periodization of Old Literary Finnish—0
Local String Transduction as Sequence Labeling—0
[LVIC-LIMSI]: Using Syntactic Features and Multi-polarity Words for Sentiment Analysis in Twitter—0
Machine Learning and Deep Neural Network-Based Lemmatization and Morphosyntactic Tagging for Serbian—0
MADAMIRA: A Fast, Comprehensive Tool for Morphological Analysis and Disambiguation of Arabic—0
Material Philology Meets Digital Onomastic Lexicography: The NordiCon Database of Medieval Nordic Personal Names in Continental Sources—0
Merging Data Resources for Inflectional and Derivational Morphology in Czech—0
Mining wisdom—0
Modernizing historical Slovene words with character-based SMT—0
Morphological Analysis and Disambiguation for Dialectal Arabic—0
Morphological Analysis Corpus Construction of Uyghur—0
Morphological Analysis for Unsegmented Languages using Recurrent Neural Network Language Model—0
Morphological Reinflection via Discriminative String Transduction—0
Moving TIGER beyond Sentence-Level—0
Multilevel Text Normalization with Sequence-to-Sequence Networks and Multisource Learning—0
Multilingwis ^2 -- Explore Your Parallel Corpus—0
Multiple Many-to-Many Sequence Alignment for Combining String-Valued Variables: A G2P Experiment—0
Multi-Team: A Multi-attention, Multi-decoder Approach to Morphological Analysis.—0
Named Entity Recognition and Linking Augmented with Large-Scale Structured Data—0
Nefnir: A high accuracy lemmatizer for Icelandic—0
NeoN: A Tool for Automated Detection, Linguistic and LLM-Driven Analysis of Neologisms in Polish—0
NeoTag: a POS Tagger for Grammatical Neologism Detection—0
Neural Lemmatization of Multiword Expressions—0
Neural Polysynthetic Language Modelling—0
N-Gramas de Caractere como T\'ecnica de Normaliza \~ao Morfol\'ogica para L\' Portuguesa: Um Estudo em Categoriza \~ao de Textos (Character N-grams as a Morphological Normalization Technique for Portuguese Language: A Study in Text Categorization)—0
Non-Standard Words as Features for Text Categorization—0
NRC: A Machine Translation Approach to Cross-Lingual Word Sense Disambiguation (SemEval-2013 Task 10)—0
NRC Russian-English Machine Translation System for WMT 2016—0
On the Effectiveness of Dataset Embeddings in Mono-lingual,Multi-lingual and Zero-shot Conditions—0
On the Role of Morphological Information for Contextual Lemmatization—0
Open-Source Tools for Morphology, Lemmatization, POS Tagging and Named Entity Recognition—0
Optimizing a Distributional Semantic Model for the Prediction of German Particle Verb Compositionality—0
Overview of the EvaLatin 2020 Evaluation Campaign—0
Overview of the EvaLatin 2022 Evaluation Campaign—0
Oxford at SemEval-2017 Task 9: Neural AMR Parsing with Pointer-Augmented Attention—0
Parser combinators for Tigrinya and Oromo morphology—0
Persian Sentiment Analyzer: A Framework based on a Novel Feature Selection Method—0
Polish Coreference Corpus in Numbers—0
POS tagging, lemmatization and dependency parsing of West Frisian—0
Predicting the Compositionality of Nominal Compounds: Giving Word Embeddings a Hard Time—0
Probabilistic Lexical Generalization for French Dependency Parsing—0
Processing and Normalizing Hashtags—0
Producing Corpora of Medieval and Premodern Occitan—0
PurePos 2.0: a hybrid tool for morphological disambiguation—0
QLUT at SemEval-2017 Task 1: Semantic Textual Similarity Based on Word Embeddings—0
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