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Lt Core News Lg

Developed by spacy
CPU-optimized Lithuanian processing pipeline with complete NLP functions including tokenization, POS tagging, dependency parsing, and named entity recognition
Downloads 52
Release Time : 3/2/2022

Model Overview

Large Lithuanian model trained on the UD Lithuanian ALKSNIS corpus, supporting full natural language processing workflows including POS tagging, dependency parsing, and named entity recognition

Model Features

Complete NLP Pipeline
Provides a full processing pipeline from tokenization to named entity recognition, including 8 processing components
CPU Optimization
Specifically optimized for CPU usage scenarios, suitable for resource-constrained environments
High-quality Word Vectors
Includes 500,000 pretrained word vectors covering a wide vocabulary
Multitask Support
Simultaneously supports multiple NLP tasks such as POS tagging, dependency parsing, and named entity recognition

Model Capabilities

Tokenization
POS Tagging
Dependency Parsing
Named Entity Recognition
Lemmatization
Morphological Analysis
Sentence Boundary Detection

Use Cases

Text Analysis
Lithuanian Text Processing
Processing and analyzing Lithuanian text content
Accurately identifies parts of speech, syntactic relationships, and named entities
Information Extraction
Entity Recognition
Extracting entity information such as person names and locations from Lithuanian text
Achieves an F1 score of 0.79
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