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Chinese Parsers DeepDoc, MinerU Crossover in Japanese RAG Performance

By PulseAugur Editorial · [1 sources] ·

A comparative analysis of two Chinese open-source document parsers, DeepDoc and MinerU, for Japanese RAG systems reveals a crossover performance based on the retrieval method used. DeepDoc demonstrated superior results with BM25 retrieval, while MinerU excelled with dense retrieval. This suggests that the optimal parser choice is dependent on the specific retrieval strategy, rather than a single parser being universally better. AI

IMPACT The choice of document parser significantly impacts RAG performance, with MinerU favored for dense retrieval and DeepDoc for BM25 in Japanese contexts.

RANK_REASON The article presents a comparative evaluation of two open-source tools for a specific technical task, including methodology and results, which constitutes research. [lever_c_demoted from research: ic=1 ai=1.0]

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Chinese Parsers DeepDoc, MinerU Crossover in Japanese RAG Performance

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The article presents a comparative evaluation of two open-source tools for a specific technical task, including methodology and results, which constitutes research. [lever_c_demoted from research: …
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · elvisyao007 ·

    Which Chinese open-source parser is better for Japanese RAG? It's a crossover — BM25 says DeepDoc, dense says MinerU

    <blockquote> <p>Final part of a series measuring Chinese open-source document parsing on Japanese documents.<br /> Repo + raw 3×2 results: <a href="https://github.com/elvisyao007/eval-driven-llm/tree/main/reports/deepdoc-eval-v2" rel="noopener noreferrer">https://github.com/elvis…

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