Knowledge Base Retrieval and Recall for Snack Food Financing Daily Reports

The data for snack food financing daily reports comes from public corporate financing announcements, disclosures from industry financial media, and

What the data for this category looks like

The data for snack food financing daily reports comes from public corporate financing announcements, disclosures from industry financial media, and information published by local financial regulatory authorities. Updates run daily, covering financing events in the snack food sector from the current day and the prior 7 calendar days. Each daily report document uses structured tables or bulleted lists for presentation. Core fields include financing entity name, financing round, financing amount, investor list, and release time. Financing amount units are uniformly ten thousand yuan or hundred million yuan. The round field uses industry-standard terminology. Release time follows the YYYY-MM-DD format.

What constraints these characteristics impose on knowledge base retrieval and recall

Data sources are scattered and use diverse formats. These include scanned PDF corporate announcements, media reports with structured tables, and regulatory disclosures in plain text paragraphs. The knowledge base parsing module must support multi-format adaptation, particularly OCR processing for scanned documents. Daily updated incremental data requires the retrieval system to support incremental recall. This avoids delays caused by full index rebuilding. Core fields include easily confused sub-brand names and financing amounts with units. Retrieval must retain field semantics to avoid unit conversion errors or brand name matching deviations. A single document contains multiple independent financing events. The system must split content along event boundaries to avoid cross-event context confusion.

How to set the configurations

Configuration ItemRecommended SettingRationale
PARSE_OCR_ENABLEEnabledAdapts to scanned financing announcement data, ensuring complete extraction of table and text content
CHUNK_SIZE800–1200 charactersThe text length of a single financing event typically ranges from 500-1000 characters. This chunk length preserves complete event context
RECALL_TOP_NTop 6 entriesDaily financing event count falls within the 5-10 entry range. Recalling the top 6 entries covers most relevant items for the day
UPLOAD_FILE_MAX_SIZE500 MBA single batch-imported collection of daily financing reports typically does not exceed this size, preventing upload timeouts
PARSE_TABLE_EXTRACT_MODESplit by rowDaily financing reports are mostly presented in structured tables. Splitting by row preserves independent field information for each financing event
SIMILARITY_THRESHOLD0.75–0.85Requires distinguishing semantic similarity between similar brand names and different financing events in the same sector to avoid false recalls

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

Three common mistakes

  • Phenomenon: Missing fields after OCR recognition, such as financing amount and investor information failing to extract properly. Cause: The PARSE_OCR_ENABLE configuration is not enabled, or the OCR resolution is set too low to recognize small table content in scanned documents.
  • Phenomenon: Retrieval response timeout, returning status code 504 Gateway Timeout. Cause: No incremental index update strategy is configured. Full index rebuilding occupies excessive system resources, leading to retrieval delays.
  • Phenomenon: Cross-financing-event context splicing after knowledge base splitting, such as combining financing information from two brands into a single entry. Cause: PARSE_TABLE_EXTRACT_MODE is not set to split by row, or chunking parameters are improperly set, forcibly truncating table row content.

How to confirm configurations are correctly set

  • Upload a scanned copy of a snack food financing daily report document, and check if all field information in the table is fully extracted in the parsing result.
  • Initiate a batch query request, verify that each query only returns financing events corresponding to the target topic, with no cross-event irrelevant results.
  • Simulate a daily incremental update scenario, upload a new daily report document, and check that the system only updates newly added entries without performing a full index rebuilding.
  • Adjust chunking parameters, then verify that split text blocks all contain complete information for a single financing event, with no content truncation or cross-event splicing.

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.