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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 101–110 of 351 papers

TitleStatusHype
DKPro Similarity: An Open Source Framework for Text Similarity—0
Do we need bigram alignment models? On the effect of alignment quality on transduction accuracy in G2P—0
DT\_Team at SemEval-2017 Task 1: Semantic Similarity Using Alignments, Sentence-Level Embeddings and Gaussian Mixture Model Output—0
ECNU at SemEval-2017 Task 4: Evaluating Effective Features on Machine Learning Methods for Twitter Message Polarity Classification—0
eFontes. Part of Speech Tagging and Lemmatization of Medieval Latin Texts.A Cross-Genre Survey—0
E-law Module Supporting Lawyers in the Process of Knowledge Discovery from Legal Documents—0
Compounds and distributional thesauri—0
EmpiriST Corpus 2.0: Adding Manual Normalization, Lemmatization and Semantic Tagging to a German Web and CMC Corpus—0
End-to-end mBERT based Seq2seq Enhanced Dependency Parser with Linguistic Typology knowledge—0
A Resource for Studying Chatino Verbal Morphology—0
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