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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

Showing 76100 of 351 papers

TitleStatusHype
On the Effectiveness of Dataset Embeddings in Mono-lingual,Multi-lingual and Zero-shot Conditions0
Enhancing Sequence-to-Sequence Neural Lemmatization with External ResourcesCode0
DBTagger: Multi-Task Learning for Keyword Mapping in NLIDBs Using Bi-Directional Recurrent Neural NetworksCode0
Constraint 2021: Machine Learning Models for COVID-19 Fake News Detection Shared Task0
Trankit: A Light-Weight Transformer-based Toolkit for Multilingual Natural Language ProcessingCode1
The Role of Interpretable Patterns in Deep Learning for MorphologyCode0
Recycling and Comparing Morphological Annotation Models for Armenian Diachronic-Variational Corpus Processing0
Utilizing Subword Entities in Character-Level Sequence-to-Sequence Lemmatization Models0
Analysing cross-lingual transfer in lemmatisation for Indian languages0
KLPT – Kurdish Language Processing ToolkitCode1
CURE: Collection for Urdu Information Retrieval Evaluation and Ranking0
TopicModel4J: A Java Package for Topic ModelsCode1
LemMED: Fast and Effective Neural Morphological Analysis with Short Context Windows0
Top2Vec: Distributed Representations of TopicsCode2
A Study of fastText Word Embedding Effects in Document Classification in Bangla LanguageCode0
Turku Enhanced Parser Pipeline: From Raw Text to Enhanced Graphs in the IWPT 2020 Shared Task0
Tagging and parsing of multidomain collectionsCode0
UDPipe at EvaLatin 2020: Contextualized Embeddings and Treebank Embeddings0
The Frankfurt Latin Lexicon: From Morphological Expansion and Word Embeddings to SemioGraphsCode0
Grammatical gender associations outweigh topical gender bias in crosslinguistic word embeddingsCode0
Neural Polysynthetic Language Modelling0
EmpiriST Corpus 2.0: Adding Manual Normalization, Lemmatization and Semantic Tagging to a German Web and CMC Corpus0
Machine Learning and Deep Neural Network-Based Lemmatization and Morphosyntactic Tagging for Serbian0
Better Together: Modern Methods Plus Traditional Thinking in NP Alignment0
BabyFST - Towards a Finite-State Based Computational Model of Ancient Babylonian0
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