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Developed by spacy
Japanese processing pipeline optimized for CPU, including tokenization, part-of-speech tagging, dependency parsing, named entity recognition, etc.
Sequence Labeling Japanese#Japanese NLP#Dependency Parsing#Named Entity Recognition
Downloads 60
Release Time : 3/2/2022

Model Overview

A small Japanese language model provided by spaCy, suitable for basic Japanese text processing tasks including tokenization, part-of-speech tagging, dependency parsing, and named entity recognition.

Model Features

CPU Optimization
Specially optimized for CPU usage, suitable for resource-limited environments
Multi-task Processing
A single model supports multiple NLP tasks including tokenization, part-of-speech tagging, dependency parsing, and named entity recognition
High Accuracy
Demonstrates high accuracy in tasks such as part-of-speech tagging and dependency parsing

Model Capabilities

Japanese Tokenization
Part-of-Speech Tagging
Dependency Parsing
Named Entity Recognition
Sentence Segmentation
Morphological Analysis

Use Cases

Text Processing
Japanese Text Analysis
Performs tokenization, part-of-speech tagging, and dependency parsing on Japanese text
Achieves up to 96.13% accuracy in part-of-speech tagging and 91.95% unlabeled attachment score (UAS)
Information Extraction
Identifies named entities from Japanese text
Entity recognition capability with an F-score of 63.41
Linguistic Research
Japanese Grammar Analysis
Used for studying Japanese grammatical structures and dependency relationships
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