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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 251–275 of 351 papers

TitleStatusHype
CEPLEXicon ― A Lexicon of Child European Portuguese—0
A Neural Lemmatizer for Bengali—0
FOLK-Gold ― A Gold Standard for Part-of-Speech-Tagging of Spoken German—0
Lemmatization and Morphological Tagging in German and Latin: A Comparison and a Survey of the State-of-the-art—0
UDPipe: Trainable Pipeline for Processing CoNLL-U Files Performing Tokenization, Morphological Analysis, POS Tagging and Parsing—0
Integrated Sequence Tagging for Medieval Latin Using Deep Representation LearningCode0
N-Gramas de Caractere como T\'ecnica de Normaliza \~ao Morfol\'ogica para L\' Portuguesa: Um Estudo em Categoriza \~ao de Textos (Character N-grams as a Morphological Normalization Technique for Portuguese Language: A Study in Text Categorization)—0
Realignment from Finer-grained Alignment to Coarser-grained Alignment to Enhance Mongolian-Chinese SMT—0
Morphological Analysis for Unsegmented Languages using Recurrent Neural Network Language Model—0
Processing and Normalizing Hashtags—0
E-law Module Supporting Lawyers in the Process of Knowledge Discovery from Legal Documents—0
Do we need bigram alignment models? On the effect of alignment quality on transduction accuracy in G2P—0
IWNLP: Inverse Wiktionary for Natural Language Processing—0
Counting What Counts: Decompounding for Keyphrase Extraction—0
Learning Representations for Text-level Discourse Parsing—0
Lexicon-assisted tagging and lemmatization in Latin: A comparison of six taggers and two lemmatization methods—0
Multiple Many-to-Many Sequence Alignment for Combining String-Valued Variables: A G2P Experiment—0
Evaluation of the Accuracy of the BGLemmatizer—0
A Publicly Available Cross-Platform Lemmatizer for Bulgarian—0
JAIST: Combining multiple features for Answer Selection in Community Question Answering—0
Enhancing Sumerian Lemmatization by Unsupervised Named-Entity Recognition—0
Persian Sentiment Analyzer: A Framework based on a Novel Feature Selection Method—0
Non-Standard Words as Features for Text Categorization—0
AI-KU: Using Co-Occurrence Modeling for Semantic Similarity—0
Illinois-LH: A Denotational and Distributional Approach to Semantics—0
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