Document Parsing and Chunking for Thermal Coal Intelligent Due Diligence Reports

Data for thermal coal intelligent due diligence reports comes from coal mine enterprise production ledgers, port spot delivery quality inspection

What the data for this category looks like

Data for thermal coal intelligent due diligence reports comes from coal mine enterprise production ledgers, port spot delivery quality inspection documents, industry supply and demand briefings, and futures delivery warehouse receipts. Update frequency varies by document type. Spot delivery documents update in real time with each batch delivery. Enterprise production reports are released monthly. Industry briefings are updated weekly. Most documents use PDF or structured table formats, and include fields such as batch identifiers, core quality inspection indicators, and supply and demand related information. Units for core fields include kilocalories per kilogram (calorific value), mass fraction (total moisture, ash content, sulfur content), and tons (delivery volume).

What constraints do these characteristics impose on the document parsing and chunking workflow

Documents from multiple sources have significant format differences. Some are plain text enterprise ledgers, while others are PDF quality inspection reports with nested tables. This requires adapting structured extraction logic for different formats. Batch-based real-time updated documents require retaining the association between batches and indicators during parsing, to avoid losing data context after chunking. Core field units are tightly bound to their associated indicators. When chunking, indicator data from the same batch must be treated as a continuous unit to prevent mixing of indicators across batches. Some industry briefings contain long paragraphs of supply and demand analysis. Chunk length must be adjusted based on indicator boundaries to avoid splitting related indicators into different chunks.

How to set configurations

Configuration ItemRecommended SettingRationale
PARSE_TABLE_ENABLEEnabledThermal coal due diligence reports contain large amounts of structured table data. Enabling this allows complete extraction of batch and indicator information within tables
CHUNK_SIZE800–1200 charactersCore indicators in thermal coal reports are tightly linked to their batches. This length preserves complete indicator groups for a single batch, avoiding splitting cross-batch data
PARSE_IGNORE_IMAGEDisabledSome quality inspection reports include sampling images, which contain auxiliary information for batch identifiers and cannot be ignored
UPLOAD_FILE_MAX_SIZE500 MBSingle files of large port delivery warehouse receipt collections typically do not exceed this value, preventing upload failures
PARSE_TIMEOUT_SECONDS300 secondsParsing time for multi-page PDF quality inspection reports is usually under 200 seconds, with reasonable buffer time reserved
CHUNK_OVERLAP10–15%Preserves contextual association of batch indicators, avoiding chunk boundaries cutting off related data

The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.

Three common mistakes

  • Phenomenon: Parsing results are empty after uploading a structured document with a modified file extension, such as renaming an HTML interface document to TXT. Cause: The document's structured markup is not recognized. Renaming only modifies the file extension, not the document's actual format structure, so the corresponding parsing logic is not triggered.
  • Phenomenon: Tasks remain in the indexing state for a long time after uploading using the chunk mode of the pushdata API. Cause: Chunk parameters are set too large, causing single chunk content to exceed system processing thresholds, or chunk overlap rate configuration is unreasonable, causing indexing queue blocking.
  • Phenomenon: No image-related information appears in parsing results after uploading a PDF document containing quality inspection sampling images. Cause: The PARSE_IGNORE_IMAGE configuration item is accidentally enabled, causing image text and auxiliary identifiers to be filtered out.

How to confirm configurations are properly set

  • Upload a single-batch thermal coal quality inspection PDF document, check the integrity of table extraction in the parsing results, and verify that core fields are fully extracted.
  • Adjust the CHUNK_SIZE and CHUNK_OVERLAP parameters, then check the chunk preview interface to confirm that indicator data from the same batch is not split across chunks.
  • Check the upload task logs to confirm that the parsing timeout configuration is greater than actual parsing time, with no timeout errors.
  • Upload a quality inspection document containing sampling images, confirm that OCR extracted content from images is included in the parsing results.

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.