Document Parsing and Chunking for Iron Ore Research Report Retrieval

Iron ore research report data mainly comes from industry associations, commodity index agencies, futures exchanges, broker research institutions, and

What this type of data looks like

Iron ore research report data mainly comes from industry associations, commodity index agencies, futures exchanges, broker research institutions, and mining enterprise announcements. Update cadences fall into three categories: daily updates (real-time data such as spot prices, port inventories), weekly updates (industry supply and demand weekly reports), and irregular releases (special research reports). Document structures typically include four parts: core indicator tables, market trend analysis, supply and demand pattern interpretation, and policy impact. Core fields include Platts iron ore index, Qingdao Port inventory, import volume, grade values, and more. Units are mostly USD/dry tonne, ten thousand tons, and similar. Some industry reports are in scanned image format, while broker research reports are mostly formatted PDF documents.

First, iron ore research reports contain a large number of precise values bound to units, such as the spot price of 62% grade iron ore. When parsing and chunking, retain the association between values and their corresponding context. Splitting these pairs will prevent complete information from being restored. Second, most core data in documents is presented in tables. Multiple columns of data in tables—such as inventories at different ports, prices of different grades—have strong correlation. Chunking must not break the complete structure of tables, otherwise data will become disconnected during retrieval. Third, document formats vary widely across sources. Both formatted PDF research reports and scanned image documents are common. The parsing link must adapt to multiple formats to avoid field loss from format incompatibility. Fourth, real-time research reports have strict timeliness requirements. Chunking must balance context coherence and timeliness. Do not combine cross-cycle market analysis into a single chunk.

How to set configurations

Configuration ItemRecommended SettingRationale
PARSE_FILE_TIMEOUT_SECONDS120 secondsMost iron ore research reports are 10-30 page PDFs. Scanned documents take longer for OCR and parsing. 120 seconds covers parsing needs for most scenarios
chunk_size800–1200 charactersCore indicator paragraphs in research reports are mostly 300-800 characters. This range retains the complete association between indicators and preceding or following market analysis
chunk_overlap150–200 charactersCore data in iron ore research reports is often mentioned across paragraphs. Overlapping sections ensure context coherence during retrieval and avoid data fragmentation
enable_ocrEnabledSome industry reports are in scanned image format. Enabling OCR extracts text content and prevents loss of core fields
parse_table_modeRetain table structurePrice and inventory tables in iron ore research reports are core retrieval units. Retaining structure ensures complete data correlation
UPLOAD_FILE_MAX_SIZE50 MBA single iron ore research report PDF is usually no larger than 20 MB. This setting reserves space for batch upload scenarios with multiple documents

The parameter values provided on this page are conventional recommendations used as a starting point 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 errors

  • Phenomenon: After uploading a scanned iron ore research report, a large number of empty fields or garbled text appear in search results. Cause: The enable_ocr configuration is not enabled. Only the image layer is parsed, and the text layer is not extracted.
  • Phenomenon: The platform returns a 504 Gateway Timeout error when parsing an iron ore research report with more than 15 pages. Cause: The PARSE_FILE_TIMEOUT_SECONDS parameter is not adjusted. The default timeout duration is insufficient for the OCR and parsing process of long documents.
  • Phenomenon: When searching for iron ore price data, entries such as "120 USD" and "62% grade" appear in different chunks. Cause: The chunk_size setting is too small, splitting the bound core indicators from their corresponding market description context.

How to confirm configurations are correctly set

  • Upload a scanned iron ore research report, check if the parsed text content contains complete core fields such as prices and inventories, to confirm that the OCR configuration is effective.
  • Upload a 20-page iron ore research report, wait for parsing to complete and check the platform logs, to confirm that the parsing duration does not exceed the value set in PARSE_FILE_TIMEOUT_SECONDS.
  • Search for core indicators in the research report (such as the Platts 62% Iron Ore Index), check if the search results contain both the indicator value and the corresponding market analysis context, to confirm that the chunking parameter configuration is reasonable.
  • Batch upload 3-5 iron ore research reports, confirm that the upload progress is normal and no file size-related error prompts are triggered.

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.