Document Parsing and Chunking for Electric Power Marketing Content

Data for electric power marketing content originates primarily from internal marketing management systems, official policy release platforms, offline

What the Data for This Category Looks Like

Data for electric power marketing content originates primarily from internal marketing management systems, official policy release platforms, offline service manuals, and similar channels of electric power enterprises. Update frequency varies by business scenario: documents related to electricity price adjustments are updated in real time, quarterly marketing activity plans are released on a fixed cycle, and daily business handling guides are revised irregularly. Documents fall into three structural categories: official documents, tariff lists with dense tables, and long-text business explanations. Fields include file number, effective date, applicable region, electricity price tier, subsidy amount, and additional relevant fields. Units include yuan per kilowatt-hour, household, ten thousand yuan, and other standard units.

Constraints Imposed on Document Parsing and Chunking by These Characteristics

For official documents, header, footer, document number, and stamped areas are non-body metadata. These must be separated separately during parsing to avoid inclusion in chunked content. For tariff lists with dense tables, standard text chunking will split associated data within individual cells, breaking subsequent retrieval logic. Long-text business explanations contain continuous process descriptions; fixed-length chunking may disrupt the coherence of business logic. Metadata such as effective date and applicable region must be bound to body chunks to prevent information misalignment during retrieval.

Configuration Settings

Configuration ItemRecommended ValueRationale
chunk_size800–1200 charactersAdapts to the average length of long-text explanations and table cells in electric power marketing documents, avoiding splitting critical information
chunk_overlap100–150 charactersRetains contextual association between adjacent chunks, meeting coherence requirements for business process-related documents
parse_table_modeRetain complete table structureAvoids splitting associated data within tables, adapting to the dense table characteristics of tariff list documents
extract_metadata_fieldsFile number, effective date, applicable regionExtracts core metadata from electric power marketing documents, binding it to body chunks
PARSE_TIMEOUT_SECONDS600 secondsAdapts to parsing time for large policy documents, preventing timeout errors triggered by oversized files
enable_chunk_duplicate_checkDisabledPreserves the chunk order from custom splitting, avoiding index disorder caused by the system automatically deleting duplicate chunks

The parameter values provided on this page are common recommendations to serve as a starting point for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on self-provided samples before finalizing settings.

Three Common Mistakes

  • Phenomenon: Parsing logs return MongoError: connect ECONNREFUSED 127.0.0.1:27017, and initialization fails. Cause: MongoDB connection parameters are not configured correctly, or the database service is not started normally.
  • Phenomenon: After custom-split documents are stored in the knowledge base, duplicate chunks are automatically removed, and the custom index order becomes disordered. Cause: The enable_chunk_duplicate_check parameter is not disabled; the system enables chunk deduplication logic by default.
  • Phenomenon: Parsed table data is output as plain text lines, and the original row and column structure of the table cannot be retained. Cause: The parse_table_mode configuration is not set to retain complete table structure, and only the basic text extraction mode is enabled.

How to Verify Proper Configuration

  • Upload an electric power tariff list document containing multiple columns of tables, view the parsed chunked content, and confirm that the table is not split, cell data is complete, and the row and column structure is retained.
  • Manually split a test document, upload it to the knowledge base, and view the chunk list, confirming that the chunk order matches the manual splitting result, with no automatically deleted chunks.
  • Call the parsing status query API, confirming that real-time update information for three statuses (parsing in progress, ready, parsing failed) can be obtained.
  • View the system parsing logs, confirming that there are no MongoDB connection errors, and parsing time does not exceed the preset PARSE_TIMEOUT_SECONDS threshold.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.