Institutional Books - Enriched Text: A Customizable Multilingual Open-Source Pipeline for Denoising, Deduplicating, and Annotating OCR Text at Scale
Score
75提出了注释式富文本替代粗暴过滤的新思路，并公开了大规模数据集和完整流水线，信息增量显著。
技术描述详实，设计理由清晰，数据集规模与处理细节均有交代，质量较高。
对需要处理图书OCR文本的研究者、训练语料构建者以及数据治理工具开发者具有直接实用价值。
2025年发布的预印本，结合最新数据发布，当前即期相关性中等。
arXiv预印本，作者来自哈佛图书馆等相关研究机构，数据源可信，但尚未经过同行评审。
Base 83.5 × T2 Source weight ×0.9 = 75
Curation line 70Selected
Why selected
The paper is hosted on arXiv, provides concrete and practical content, innovatively replaces aggressive filtering with annotated enriched text, and releases both a dataset and an open-source pipeline, yielding high information gain.
AI commentary
「What stands out here is the reflection on heavy-handed data preprocessing in AI and a concrete, engineering-ready solution. For teams training models on large-scale historical texts or conducting digital humanities research, IB-HL-ET and the open-source pipeline can save enormous duplicated cleanup effort while preserving user control over the data.」
Quick overview
Harvard Library, in partnership with the Google Books Library project, digitized approximately 983,004 volumes, forming the IB-HL dataset (242B o200k_base tokens). To address the issues of aggressive filtering and metadata loss in existing preprocessing pipelines, the researchers propose the Enriched Text approach: instead of a single processed stream, the text is normalized while preserving metadata through HTML-like annotations. Per-paragraph language detection, duplicate paragraph cluster identification, and bits-per-byte scores are provided. Users can parse these annotations and tailor outputs to their needs. The release includes IB-HL-ET, an enriched-text version containing 217B tokens across 983,003 volumes, organized into 1.39B annotated subtopic paragraphs, covering about 250 languages, along with the open-source pipeline that produced it.
- IB-HL contains 983,004 volumes and 242B o200k_base tokens, from Harvard Library's Google Books collaboration
- Enriched Text avoids over-filtering by layering HTML-like annotations for per-paragraph language, duplicate clusters, and compression scores
- IB-HL-ET release: 217B tokens across 983,003 volumes, organized into 1.39B annotated subtopic paragraphs, covering ~250 languages
- The open-source pipeline lets users parse annotations and customize outputs instead of accepting a global editorial decision
Full text
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