P

Pt Core News Sm

Developed by spacy
spaCy's CPU-optimized Portuguese processing pipeline, including tokenization, POS tagging, dependency parsing, named entity recognition, etc.
Downloads 87
Release Time : 3/2/2022

Model Overview

This is a Portuguese natural language processing model primarily used for text classification tasks such as POS tagging, named entity recognition, and dependency parsing.

Model Features

CPU Optimization
Processing pipeline specifically optimized for CPU usage scenarios
Comprehensive NLP Features
Provides complete NLP processing capabilities from tokenization to named entity recognition
High-Accuracy Lemmatization
Lemmatization accuracy reaches 96.76%
Multitasking Support
Simultaneously supports various tasks such as POS tagging, dependency parsing, and named entity recognition

Model Capabilities

Named Entity Recognition
POS Tagging
Morphological Analysis
Lemmatization
Dependency Parsing
Sentence Segmentation

Use Cases

Text Processing
Portuguese Document Analysis
Performs POS tagging and named entity recognition on Portuguese documents
NER F1 score 0.88, POS accuracy 0.96
Portuguese Grammar Analysis
Analyzes dependency relationships in Portuguese sentences
LAS score 0.84, UAS score 0.89
Information Extraction
Portuguese Entity Recognition
Extracts entities such as person names and locations from Portuguese text
NER precision 0.88, recall 0.88
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
© 2025AIbase