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Pl Core News Lg

Developed by spacy
CPU-optimized Polish natural language processing model supporting POS tagging, named entity recognition, dependency parsing and other tasks
Downloads 58
Release Time : 3/2/2022

Model Overview

A large Polish processing pipeline based on the spaCy framework, including tokenization, POS tagging, morphological analysis, dependency parsing, named entity recognition, optimized for CPU usage.

Model Features

CPU optimization
Processing pipeline specifically optimized for CPU usage
Comprehensive language analysis
Supports comprehensive Polish language analysis including morphological features and complex grammatical structures
High-quality vectors
Contains 500,000 unique vectors (300 dimensions) providing good semantic representation
Multi-task processing
Single model can simultaneously handle multiple tasks like POS tagging, named entity recognition, and dependency parsing

Model Capabilities

POS tagging
Named entity recognition
Dependency parsing
Lemmatization
Morphological analysis
Sentence segmentation

Use Cases

Text processing
Polish document analysis
Grammatical analysis and structural parsing of Polish texts
Accurate identification of POS tags, grammatical relations and named entities
Information extraction
Extract structured information from Polish texts
Named entity recognition accuracy with F1 score of 0.841
Linguistic research
Polish morphological analysis
Analyze complex Polish morphological variations
Morphological feature accuracy rate of 90.98%
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