Knowledge Base Retrieval and Recall for Film and Theater Research Report Retrieval

Film and theater research report data comes from securities firm industry research reports, theater operation backend data, public data from the

What Data Looks Like for This Category

Film and theater research report data comes from securities firm industry research reports, theater operation backend data, public data from the national film ticketing comprehensive information management system, and monthly statistical documents from industry associations. Update frequency varies by report type. The system updates special reports for new film release nodes in real time. Quarterly industry panoramic reports are released quarterly. The system updates daily operational data each day. Most documents combine structured tables and paragraphs. They include fields such as schedule screening sessions, individual theater box office, audience age breakdown, revenue sharing ratio, and more. Units include person-times, ten thousand yuan, sessions, and others.

Constraints on Knowledge Base Retrieval and Recall

The multi-source and heterogeneous nature of film and theater research reports requires the knowledge base retrieval system to support both structured table field matching and unstructured text semantic recall. Data sources with different update rhythms require the retrieval link to flexibly switch between incremental synchronization and full synchronization. This avoids real-time data lag. The document structure with multiple fields and units requires recall results to be sorted by field relevance. This prevents confusion between data from different dimensions. Additionally, if multiple columns of structured tables are not properly chunked, retrieval requests targeting specific fields will fail to match. This reduces retrieval accuracy.

Configuration Settings

Configuration ItemRecommended SettingRationale
UPLOAD_EXCEL_PARSE_MODEIntelligent Chunking and Column-wise RecognitionAdapts to multi-column structured tables in film and theater research reports, preserving independent semantics for each column field
CHUNK_SIZE800–1200 charactersBalances semantic integrity for long-form box office analysis and short-form schedule data, avoiding overly fragmented or overly long chunks
RECALL_TOP_NTop 8 resultsCovers multiple research report query dimensions including schedules, box office, and audience profiles, avoiding too few recall results
RERANK_TRIGGER_THRESHOLD0.7Controls the trigger condition for the reranking model, avoiding redundant calculations when initial recall results already meet requirements
PARSE_TABLE_ENABLEDEnabledExtracts cell fields from structured tables in film and theater research reports, supporting precise retrieval by specified column names
UPLOAD_FILE_MAX_SIZE500 MBAdapts to typical size of single theater research report collections, avoiding upload timeouts or parsing failures

The parameter values provided on this page are common starting points 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 your own samples before finalizing settings.

Common Three Pitfalls

  • Phenomenon: After uploading a multi-column structured Excel research report, retrieval fails to match specified column box office data. Cause: The PARSE_TABLE_ENABLED switch is not enabled, or the parsing mode only recognizes the first two columns.
  • Phenomenon: After chunking a long document, the number of recall results meets requirements, but the reranking model is not triggered. Cause: A reasonable RERANK_TRIGGER_THRESHOLD is not set, or initial recall similarity exceeds the threshold upper limit.
  • Phenomenon: After creating a knowledge base via the API, the chat API cannot associate the specified knowledge base. Cause: The corresponding knowledge base ID is not bound in the chat API configuration, or the correct association parameter is not passed during API invocation.

How to Confirm Proper Configuration

  • Upload a test film and theater Excel research report, check parsed chunked content to confirm multiple column fields are correctly recognized.
  • Initiate a query including specific fields such as "summer box office", verify that recall results include content matching the specified fields.
  • Adjust RERANK_TRIGGER_THRESHOLD to an appropriate range, initiate a query related to long documents, check whether the reranking model is triggered.
  • Create a test knowledge base via the API, call the chat API with the association parameter, confirm returned results include content from this knowledge base.

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.