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Hu Core News Lg

Developed by huspacy
Large-scale Hungarian natural language processing model based on the spaCy framework, supporting multiple NLP tasks.
Sequence Labeling Other#Hungarian NLP#High-accuracy POS tagging#Multitask language processing
Downloads 2,475
Release Time : 3/2/2022

Model Overview

This is a large-scale natural language processing model for Hungarian, developed on the spaCy framework, capable of performing various NLP tasks such as POS tagging, named entity recognition, and dependency parsing.

Model Features

High-accuracy Named Entity Recognition
Achieves 87% F1 score in NER tasks, accurately identifying named entities in Hungarian texts.
Comprehensive Linguistic Analysis
Supports various linguistic analysis tasks including POS tagging, morphological analysis, and lemmatization.
Efficient Sentence Segmentation
Sentence segmentation F-score reaches 98.66%, accurately delineating sentence boundaries in texts.

Model Capabilities

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

Use Cases

Text Processing
Hungarian Text Analysis
Performs grammatical analysis and structural parsing of Hungarian texts.
Accurately identifies POS tags, entities, and sentence structures.
Information Extraction
Extracts key information and entities from Hungarian texts.
High-precision extraction of named entities such as person and location names.
Linguistic Research
Hungarian Grammar Research
Analyzes Hungarian grammatical structures and morphological variations.
Provides detailed POS tagging and morphological feature analysis.
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