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Original analysisAI-assisted
Processing Long Documents: Preserve Chapter Relationships across Chunks
When a long document exceeds the processing range, simply cutting it by word count may break up definitions, tables, and cross-page relationships. This article discusses methods of segmenting by structure, saving paragraph positions, and verifying before summarizing, explaining when parallel processing is appropriate and what content requires contextual connection. The input restrictions in technical data are only the starting point. In the end, it is necessary to check whether the business information is complete. The completion of the segmentation cannot be regarded as the completion of data understanding.
ChinaOPC Editorial TeamOriginal analysis2 min readChina2 views
Source timingPublic information and official documents; verified on October 23, 2026.
The text embedding model card explains the input length limit, and the queue document explains how the task is performed. The following is ChinaOPC’s design of long data workflow, and is not an independent effect test of a certain model.
First create a chapter and original text position index
Simulate device data, record chapters, sections, page numbers and definition positions, and then determine the segmentation range. Try to keep the header and data, conditions and exceptions as relevant as possible; when they must be split, the accompanying context should be clear, and the model should not be allowed to guess the missing information in the previous paragraph.
Parallel results retain source relationships
Each task has a file version and paragraph number, and the results are summarized according to the original structure. A list will be given when the processing fails or a paragraph is missing, and it will not be filled in with the generated content of adjacent paragraphs. Different tasks should not each create conflicting definitions of terms.
Recheck cross-segment issues after aggregation
Check chapter coverage, repeated content, consistency of terminology and reference positions, and return key figures to the original text for confirmation. When it comes to official original texts, segmentation can only be used for retrieval and analysis, and the text cannot be automatically rewritten. This article does not promise that long-form paragraphing will eliminate all missing context.
AI assists in organizing and writing, and editors check public sources. The main text is an independent analysis by ChinaOPC, with source facts and simulation plans separated; no interviews, financial audits or actual product testing have been conducted. Official documents are based on the original text of the source and have not been adapted or replaced. English translation of the Chinese edition, prepared with machine assistance and editorial checks. Source verification dates refer to the original Chinese research.
Source titles and publisher names are retained in their original language. Refer to the linked originals for official documents and current requirements.
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