Albertaworlds

Albertaworlds / Japanese-Corpus-Syntactic-Analysis-Agent

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日本語コーパス形態素解析・依存構文解析・可視化エージェント | Japanese Corpus Morphological & Syntactic Dependency Analysis & Visualization Agent

12
0
89% credibility
Found May 15, 2026 at 22 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

An AI agent for performing comprehensive syntactic analysis on Japanese text corpora, covering cleaning, morphology, dependency parsing, metrics, and visualizations.

How It Works

1
📰 Discover the Japanese text analyzer

You find a friendly assistant that helps study Japanese writing by breaking texts into words, sentences, and styles.

2
📝 Share your Japanese text

Paste or upload a story, article, or book excerpt in Japanese, and the assistant gets ready to explore it.

3
✨ Watch it clean and prepare

The assistant tidies up the text, splits it into sentences, and shows a preview of the neat, ready-to-analyze content.

4
🔍 Dive into word breakdowns

See details on every word type—like nouns, verbs, and adjectives—plus vocabulary richness and part-of-speech mixes.

5
📈 Examine sentence connections

Discover how words link in sentences, with scores on complexity, dependency distances, and overall structure.

6
🖼️ View colorful diagrams

Get beautiful charts and tree diagrams showing word trees and comparisons that make patterns pop.

🎉 Unlock writing insights

You now understand the text's style, complexity, and unique features, perfect for learning or research.

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Star Growth

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AI-Generated Review

What is Japanese-Corpus-Syntactic-Analysis-Agent?

This Python agent automates full syntactic analysis of Japanese language corpora, handling cleaning, morphological parsing with MeCab and UniDic, dependency parsing via SpaCy, metric computation like TTR, MLS, MDD, and visualizations of trees and comparisons. Feed it raw Japanese text from datasets, subtitles, or speech corpora, and get cleaned sentences, stats, charts, and dependency graphs via a FastAPI server or local CLI scripts like http_run.sh and local_run.sh. It's built for developers diving into github japanese resources, immersion tools, or old japanese corpus analysis.

Why is it gaining traction?

It bundles everything into a LangChain/LangGraph agent with ready tools—no piecing together MeCab, SpaCy, and matplotlib yourself—plus S3 uploads for viz outputs and OpenAI-compatible endpoints. The full pipeline spits out precise metrics matching official benchmarks, with dependency trees in Japanese labels, standing out in awesome japanese github lists for conjugation and syntactic tasks. Low setup via uv sync makes it quick for prototyping japanese tv subtitle analysis or corpus datasets.

Who should use this?

Linguists analyzing japanese speech corpus or english-japanese parallel data for immersion apps. NLP devs building github japanese tv stream parsers or subtitle tools needing quick morphology and dependency metrics. Researchers on japanese corpus wiki entries or old japanese corpus projects evaluating syntactic complexity.

Verdict

Grab it if you're in Japanese NLP—solid for agent-based analysis with 12 stars signaling early but focused maturity. 0.9% credibility score reflects nascent docs and tests, so test locally first; pair with your own validation for production.

(198 words)

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