What data in this category looks like
Data sources for financial field film theater project due diligence cover national official movie ticketing systems, third-party theater operation platforms, and official filing and public notice pages of the National Film Bureau. Update schedules follow three cycles: daily updates for same-day box office and session data, weekly updates for theater cooperation schedule data, and monthly updates for film filing and qualification information. Documents are mostly structured tables and semi-structured text. Fields include unique film identifier, film title, release period, cooperating theater list, daily box office data, and per-screen average audience count. Units include yuan, person-times, sessions, and others.
What constraints do these characteristics impose on the "citation source and traceability" link
The multi-source, dispersed nature of financial film theater due diligence data requires binding unique film identifiers as association keys during traceability to avoid confusion between identically named films from different data sources. Different data sources have varying update cycles. Independent synchronization and verification cycles must be set for different data types such as box office, schedules, and filings to prevent citing expired information. Mixed semi-structured and structured document formats require targeted field extraction rules to ensure accurate positioning of corresponding data entries during traceability. Numeric fields with units require unified unit conversion logic to avoid traceability failure caused by unit differences between the same type of data from different sources.
Configuration settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
source_trace_enable | Enabled | Enables attaching data source links and field information to outputs, meeting the traceability requirements of film theater due diligence |
Recall count | Top 6 entries | Covers multi-dimensional data such as box office, schedule, and filing for a single film, adapting to the multi-source and dispersed data source characteristics |
Similarity threshold | 0.75–0.85 | Prevents cross-film traceability errors caused by similar film names, adapting to the similarity characteristics of film project names |
Segmented Parsing Length | 800–1200 characters | Adapts to the layout of semi-structured documents for film theaters, ensuring field extraction does not split critical data |
Field Association Key | Unique film identifier | Binds unique identifiers for multi-source data, resolving traceability confusion between identically named films from different data sources |
Data Sync Cycle | Once daily | Adapts to daily updated box office and session data, ensuring traceability data is up to date |
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 case-by-case analysis. It is recommended to test on local samples before finalizing settings.
Three common mistakes
- Phenomenon: When the workflow runs, only the first query associates knowledge base citations, and subsequent queries have no traceability information. Cause: The knowledge base retrieval reuse logic for conversation context is not configured, causing subsequent queries to not trigger the knowledge base recall process.
- Phenomenon: Global variables configured in the workflow cannot be referenced in the knowledge base retrieval node. Cause: The node visibility permission for global variables is not enabled, or the variable scope does not cover the current workflow node.
- Phenomenon: The units of retrieval results do not match expectations, causing traceability data to fail to match. Cause: Unified unit conversion rules are not configured, and the same type of data from different sources cannot be associated due to unit differences.
How to confirm the configuration is complete
- Trigger a due diligence query for a single film, check whether data source links and field information are attached to the output results, confirming that the traceability configuration takes effect.
- Import test documents containing multi-source film data, verify whether the retrieval results cover different types of business fields, confirming that the field extraction rules are configured correctly.
- Run multi-round test queries, check whether each query can associate corresponding knowledge base traceability information, confirming that the conversation context retrieval logic works properly.
- View the data synchronization records, confirm that the latest data source updates have been synchronized to the knowledge base, ensuring that traceability data is up to date.
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.