SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–225 of 351 papers

TitleStatusHype
JHUBC's Submission to LT4HALA EvaLatin 2020—0
Joint Diacritization, Lemmatization, Normalization, and Fine-Grained Morphological Tagging—0
Joint Lemmatization and Morphological Tagging with LEMMING—0
KeyXtract Twitter Model - An Essential Keywords Extraction Model for Twitter Designed using NLP Tools—0
KLUE-CORE: A regression model of semantic textual similarity—0
Korp --- the corpus infrastructure of Spr—0
LABDA at SemEval-2017 Task 10: Relation Classification between keyphrases via Convolutional Neural Network—0
LAMB: A Good Shepherd of Morphologically Rich Languages—0
LatinCy: Synthetic Trained Pipelines for Latin NLP—0
Learning Morphosyntactic Analyzers from the Bible via Iterative Annotation Projection across 26 Languages—0
Learning Representations for Text-level Discourse Parsing—0
Learning to Lemmatize in the Word Representation Space—0
Lemmatization and Morphological Tagging in German and Latin: A Comparison and a Survey of the State-of-the-art—0
Lemmatization and Morphosyntactic Tagging of Croatian and Serbian—0
Lemmatization and POS-tagging process by using joint learning approach. Experimental results on Classical Armenian, Old Georgian, and Syriac—0
Lemmatization of Multi-word Common Noun Phrases and Named Entities in Polish—0
LemMED: Fast and Effective Neural Morphological Analysis with Short Context Windows—0
Leveraging Data-Driven Methods in Word-Level Language Identification for a Multilingual Alpine Heritage Corpus—0
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
Show:102550
← PrevPage 9 of 15Next →

No leaderboard results yet.