NCTB-SchoolText-EN: A Curriculum-Aligned English Text Corpus from the Official English-Medium School Textbooks of Bangladesh (Classes 1–10)

NCTB-SchoolText-EN is a passage-level English text corpus extracted from the official English-medium editions of the general-curriculum textbooks published by the National Curriculum and Textbook Board (NCTB) of Bangladesh, covering Classes 1 through 10. The dataset contains 50,502 passage chunks drawn from 800 chapters across 86 books, 25 distinct subjects and nine grade levels (Classes 1-8 individually, and Classes 9-10 combined as the SSC book set), stored in a uniform JSON Lines (JSONL) schema. Each record reports the grade, subject, language, chapter number, chapter title, a deterministic chunk identifier, and the cleaned passage text, allowing any chunk to be traced back to its exact position in the curriculum. Every book in this release is one that NCTB itself publishes in English, so the text is the board's own official English wording rather than a translation. The source materials are scanned, image-based PDFs. Because direct text extraction from these files is unreliable, the corpus was built using optical character recognition (Tesseract, via pytesseract) with the English language model, followed by chapter mapping from per-book configuration files and cleaning to remove scanning artefacts (headers, footers, page numbers) while preserving punctuation and question/list structure. Text is then segmented into short, pedagogically coherent chunks (median length 356 characters) that keep activities, questions, and expository passages intact rather than splitting them mid-unit. All 13,042 source pages were successfully processed, with a residual OCR garbage rate of 0.7%. The corpus is monolingual English throughout: every one of the 50,502 records was checked to contain no Bengali script. It is intended as a machine-readable, curriculum-aligned foundation for educational NLP applications such as retrieval-augmented tutoring systems, curriculum-grounded question answering, comprehension-set generation, and language modelling research on school-level educational text. Only processed text chunks and chapter-mapping configuration files are released; raw NCTB PDF scans are not redistributed for copyright reasons.NCTB-SchoolText-EN 是一款篇章级英文语料库，其数据源自孟加拉国国家课程与教材委员会（National Curriculum and Textbook Board, NCTB）出版的通用课程英文原版教材，覆盖1至10年级。该数据集包含来自86册教材、25门不同学科、9个学段（1至8年级各为独立学段，9至10年级合并为中等教育证书考试（SSC）教材套装）的800个章节，总计50502个篇章片段，采用统一的JSON Lines（JSONL）格式存储。每条记录包含学段、学科、语言、章节编号、章节标题、确定性片段标识符以及清洗后的篇章文本，可将任意片段溯源至其在课程体系中的精确位置。 本次发布的所有教材均为NCTB官方出版的英文原版教材，因此文本采用委员会自有官方英文措辞，而非译制版。原始素材为扫描得到的图像型PDF文件。由于直接从这类文件中提取文本可靠性不足，该语料库通过光学字符识别（Optical Character Recognition, OCR）工具构建：采用基于英语语言模型的Tesseract（通过pytesseract调用）完成识别，随后通过单册教材配置文件完成章节映射，并进行清洗以去除扫描伪影（页眉、页脚、页码），同时保留标点符号与问题/列表结构。随后将文本切分为符合教学逻辑的短片段（中位数长度为356字符），保留活动、问题与说明性篇章的完整性，避免在教学单元中途拆分内容。本次处理成功覆盖全部13042份源页面，OCR残留垃圾率为0.7%。 该语料库全程为单语英文：已对全部50502条记录进行检查，确保未包含孟加拉语文字。其旨在作为可机器读取、与课程对齐的基础资源，服务于教育领域自然语言处理（Natural Language Processing, NLP）应用，例如检索增强型辅导系统、基于课程的问答系统、阅读理解题生成，以及针对中小学教育文本的语言建模研究。本次仅发布处理后的文本片段与章节映射配置文件；出于版权原因，原始NCTB扫描PDF文件不予重新分发。