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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 226–250 of 351 papers

TitleStatusHype
The 2021 Urdu Fake News Detection Task using Supervised Machine Learning and Feature Combinations—0
The annotation of the C-ORAL-BRASIL oral through the implementation of the Palavras Parser—0
The CMU Machine Translation Systems at WMT 2014—0
The COPLE2 corpus: a learner corpus for Portuguese—0
The effect of stemming and lemmatization on Portuguese fake news text classification—0
The Effects of Syntactic Features in Automatic Prediction of Morphology—0
The First Cross-Lingual Challenge on Recognition, Normalization, and Matching of Named Entities in Slavic Languages—0
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
The GW/UMD CLPsych 2016 Shared Task System—0
The impact of simple feature engineering in multilingual medical NER—0
The IPR-cleared Corpus of Contemporary Written and Spoken Romanian Language—0
The Kyoto University Cross-Lingual Pronoun Translation System—0
The Netlog Corpus. A Resource for the Study of Flemish Dutch Internet Language—0
The Political Speech Corpus of Bulgarian—0
The Power of Language Music: Arabic Lemmatization through Patterns—0
The Reading Machine: A Versatile Framework for Studying Incremental Parsing Strategies—0
The SETimes.HR Linguistically Annotated Corpus of Croatian—0
The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection—0
The SYN-series corpora of written Czech—0
The Use of Text Alignment in Semi-Automatic Error Analysis: Use Case in the Development of the Corpus of the Latvian Language Learners—0
Tokenizing, POS Tagging, Lemmatizing and Parsing UD 2.0 with UDPipe—0
To lemmatize or not to lemmatize: how word normalisation affects ELMo performance in word sense disambiguation—0
Tolerant BLEU: a Submission to the WMT14 Metrics Task—0
Towards an automatic identification of chiasmus of words (Vers une identification automatique du chiasme de mots) [in French]—0
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