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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 226250 of 351 papers

TitleStatusHype
Authorship Attribution Based on Life-Like Network Automata0
An Analysis of Lemmatization on Topic Models of Morphologically Rich Language0
An NLP Pipeline for Coptic0
NRC Russian-English Machine Translation System for WMT 20160
Leveraging Inflection Tables for Stemming and Lemmatization.0
Morphological Reinflection via Discriminative String Transduction0
Predicting the Compositionality of Nominal Compounds: Giving Word Embeddings a Hard Time0
English-French Document Alignment Based on Keywords and Statistical Translation0
Dealing with word-internal modification and spelling variation in data-driven lemmatization0
UdS-(retrain|distributional|surface): Improving POS Tagging for OOV Words in German CMC and Web Data0
SoMaJo: State-of-the-art tokenization for German web and social media textsCode0
Using longest common subsequence and character models to predict word forms0
The Kyoto University Cross-Lingual Pronoun Translation System0
The GW/UMD CLPsych 2016 Shared Task System0
Leveraging Data-Driven Methods in Word-Level Language Identification for a Multilingual Alpine Heritage Corpus0
ASOBEK at SemEval-2016 Task 1: Sentence Representation with Character N-gram Embeddings for Semantic Textual Similarity0
Unsupervised Compound Splitting With Distributional Semantics Rivals Supervised MethodsCode0
Weighting Finite-State Transductions With Neural Context0
HHU at SemEval-2016 Task 1: Multiple Approaches to Measuring Semantic Textual Similarity0
The IPR-cleared Corpus of Contemporary Written and Spoken Romanian Language0
Merging Data Resources for Inflectional and Derivational Morphology in Czech0
Analyzing Pre-processing Settings for Urdu Single-document Extractive SummarizationCode0
Rule-based Automatic Multi-word Term Extraction and Lemmatization0
Urdu Summary CorpusCode0
The COPLE2 corpus: a learner corpus for Portuguese0
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