What Data for This Category Looks Like
Data sources for text annotation projects primarily include customer corpora, content exported from annotation platforms, specialized vocabularies, and quality inspection sampling results. Daily processed documents cover annotation specifications, sample packages, quality inspection reports, and problem feedback forms. Most documents use structured tables, segmented explanations, or rule entries with hierarchical headings. Common fields include entity labels, semantic boundary definitions, sample IDs, and quality inspection scores. Update frequency is typically daily or per annotation batch. This category focuses on semantic boundary, entity, and intent recognition, which differs from the visual feature processing requirements of image annotation projects.
Constraints Imposed on Document Parsing and Chunking
Structured tables and segmented rules in daily documents require the parsing process to retain column alignment and paragraph hierarchy, to avoid breaking semantic associations. Daily or batch update requirements mean the parsing workflow must support batch task scheduling and incremental synchronization, to avoid re-parsing full datasets. Frequent changes to annotation specifications and problem feedback forms require the parsing process to adapt to dynamic format adjustments, while retaining context information related to labels. This prevents chunking from truncating entity definitions or annotation rules. The long text nature of quality inspection reports requires chunking to balance semantic completeness and context correlation, to avoid splitting related entries from quality inspection sampling results.
Configuration Settings
For FastGPT v4.17.0, the following configuration items can directly adapt to the parsing needs of text annotation projects:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Documents for text annotation projects often contain entity definitions and semantic rules. This length preserves complete semantics for a single label rule or sample explanation |
chunkSplitter | Split by paragraph + heading | Daily documents mostly include hierarchical headings and segmented explanations for annotation specifications. Retaining paragraph structure avoids semantic splitting |
customPdfParse | Enabled | Uploaded annotation specifications or sample packages are often in PDF format. Enabling this preserves the corresponding association between images and text, adapting to document parsing with illustrations |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Single files for bulk sample packages are often large. This upper limit covers standard bulk upload requirements |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Long documents or bulk parsing tasks require sufficient time to complete format recognition and chunking, to avoid mid-process timeout interruptions |
chunkSettingMode | Manual configuration | Document formats for text annotation projects vary widely. Manual configuration allows flexible adjustment of chunking rules to adapt to different types of annotation documents |
Three Common Misconfigurations
- Symptom: After uploading a PDF document with images, the parsing result only returns text content, with no image association information. Cause: The
customPdfParseconfiguration is not enabled. The default parsing logic does not retain the binding relationship between images and text. - Symptom: After parsing a multi-column annotation specification document, the column alignment relationship is lost, and table content is disorganized. Cause: No chunking rules adapted for structured tables are configured. The default chunking logic does not recognize multi-column layouts.
- Symptom: Some parsing tasks time out and fail after uploading a bulk sample package. Cause: The
PARSE_FILE_TIMEOUT_SECONDSvalue is not adjusted to a duration adapted for bulk tasks. The default timeout threshold is insufficient to complete long document parsing.
How to Verify Configurations Are Correct
- Upload a single annotation specification PDF with images, confirm the parsing result includes associated descriptions or placeholder information for images, to verify the
customPdfParseconfiguration is active. - Upload a multi-column format document, confirm the parsed text retains the original table's column alignment structure, to verify the chunking rules adapt to structured documents.
- Upload a bulk sample package, review the execution status of the task queue, confirm no bulk timeout errors occur, to verify the timeout threshold configuration is reasonable.
- Adjust the
chunkSizeparameter, confirm the semantic completeness of the chunking results meets the rule requirements of the annotation documents, to verify the chunk length configuration adapts to current business documents.
The values provided here are common starting points, and should be evaluated 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 2026-10-19.