Q&A on Policy and Institutional Basis for Legitimacy Review of Regulatory Documents: Document Parsing and Chunking

What the data for this category looks like

Daily processed documents for this category include regulatory document drafts, drafting explanations, legitimacy review opinions, solicited opinion summaries, and filing reports. Data sources include regulatory and rule databases, higher-level law databases, departmental policy document databases, and administrative regulatory document filing systems. Update frequency is irregular. Document structures vary significantly: some are text-based regulatory document main texts, others are summarized opinion lists. Some documents include tabular clause comparison sheets or opinion summary tables. There is no fixed unified field format, so parsing must adapt to multiple document structures.

What constraints these characteristics impose on the "document parsing and chunking" link

The data characteristics of this category impose multiple constraints on document parsing and chunking. First, document formats from multiple sources are inconsistent. Parsing components must support adaptation to text-based, summarized, and tabular documents. Second, update frequency is irregular. Parsing components must accommodate format differences between historical documents from different batches and newly added documents. Third, documents are used for legitimacy review. Chunking must accurately align with review dimensions such as formulation authority, procedures, and clauses. Content splicing across core review units is prohibited. Finally, errors carry significant consequences. The parsing link must avoid content omission or incorrect splitting, to ensure the accuracy of subsequent comparison and review.

Reference only; verify against the target FastGPT release and deployment documentation.

How to set the configurations

Three common mistakes

• Table content is not parsed after uploading a regulatory document, and fields are empty. The cause is that the table recognition switch for customPdfParse is not enabled, resulting in incomplete extraction of embedded clause comparison sheets and opinion summary tables.
• Parsing tasks return timeout errors with a status code of 504. The cause is that PARSE_FILE_TIMEOUT_SECONDS is not adjusted to a value suitable for large files; the default parameter cannot cover the parsing duration of multi-chapter filing reports.
• Chunking results show content splicing across legal articles, and the number of results does not match expectations. The cause is that the default chunkSplitter uses pure character-based splitting, which does not adapt to the title hierarchy and paragraph structure of documents, leading to core review units being split or merged.

How to confirm the configuration is correct

• Upload a solicited opinion summary document that includes embedded tables, and check if the parsed results include complete table content and text descriptions.
• Adjust the chunkSize parameter, then check if the chunking results are split by document titles and paragraphs, with no content splicing across legal articles.
• Upload a filing report file of the maximum allowed configuration size, and confirm that the parsing task does not trigger an error restricted by UPLOAD_FILE_MAX_SIZE.
• View parsing logs, confirm that the set value of PARSE_FILE_TIMEOUT_SECONDS matches the parsing duration of the current document, and no timeout interruptions occur.

The values provided are common starting points and should be measured against the reader's own samples.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.