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

Showing 101110 of 351 papers

TitleStatusHype
Acquisition of semantic relations between terms: how far can we get with standard NLP tools?0
Do we need bigram alignment models? On the effect of alignment quality on transduction accuracy in G2P0
A Case Study of Spanish Text Transformations for Twitter Sentiment Analysis0
ECNU at SemEval-2017 Task 4: Evaluating Effective Features on Machine Learning Methods for Twitter Message Polarity Classification0
eFontes. Part of Speech Tagging and Lemmatization of Medieval Latin Texts.A Cross-Genre Survey0
E-law Module Supporting Lawyers in the Process of Knowledge Discovery from Legal Documents0
Developing New Linguistic Resources and Tools for the Galician Language0
EmpiriST Corpus 2.0: Adding Manual Normalization, Lemmatization and Semantic Tagging to a German Web and CMC Corpus0
End-to-end mBERT based Seq2seq Enhanced Dependency Parser with Linguistic Typology knowledge0
Automatic Extraction of Synonyms for German Particle Verbs from Parallel Data with Distributional Similarity as a Re-Ranking Feature0
Show:102550
← PrevPage 11 of 36Next →

No leaderboard results yet.