Citation Sources and Traceability for Plastics and Rubber

What the data for this category looks like

Plastics and rubber research report data mainly comes from China Plastics Processing Industry Association, China Rubber Industry Association, domestic futures exchanges, and leading third-party industrial consulting institutions. It is core reference material for financial business related to plastics and rubber futures and wealth management. Update cycles cover spot daily reports, weekly supply and demand monitoring, monthly price reports, quarterly industry outlook, and annual industry white papers.

Document structures typically include standardized fields: capacity statistics (unit: 10,000 tons/year), operating rate (unit: %), spot price (unit: yuan/ton), import and export volume (unit: 10,000 tons), downstream demand proportion, and accompanying analyst comments on policies and raw material fluctuations. Some segmented category reports will mark supply and demand data for specific grades.

Constraints imposed by these characteristics on citation and traceability

The multi-source, multi-update-cycle, and segmented field characteristics of plastics and rubber research reports impose three constraints on citation and traceability. First, data from different institutions and cycles varies significantly. It is necessary to clearly mark the publishing institution and publishing time during traceability to avoid confusing statistical data of the same category from different batches. Second, documents contain both standardized industrial data and non-standardized analyst comments. During traceability, core data fields must be accurately matched, and reliance solely on text similarity must be avoided to ensure that the referenced content is the original material for specific grades and prices. Third, there are many details for segmented grades. Complete document metadata must be retained to avoid mixing research report data from different origins and specifications. Redundant content from non-professional data sources must also be filtered to ensure traceability credibility.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`Recall Count`	`Top 10-15`	Plastics and rubber research reports have high single-piece data density. Too many recalled entries will cause redundant context, while too few will fail to cover multi-dimensional information such as supply and demand, prices, and policies
`Similarity Threshold`	`0.72-0.85`	Research report text contains a large number of professional terms and segmented fields. A threshold that is too low will introduce irrelevant industrial general content, while a threshold that is too high may miss accurate reports targeting specific grades
`Citation Source Display Fields`	`["Publishing Institution", "Publishing Time", "Document Title", "Core Data Field"]`	The authority and specific dimensions of plastics and rubber industrial data are core requirements for traceability. Display verifiable metadata and data points
`Reranked Return Count`	`Top 5-8`	Relevance ranking for professional research reports needs to prioritize matching core data fields, not only rely on general text similarity. Limiting the number of reranked entries focuses on the most relevant traceability content
`Data Source Filtering Rules`	`Only include reports from industry associations, futures exchanges, and compliant third-party consulting institutions`	The authority of plastics and rubber industrial data directly affects traceability credibility. Filter redundant content from non-professional data sources

The parameter values provided on this page are common recommendations used to set a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.

Three Common Mistakes

Phenomenon: Retrieved citation entries include data sources not uploaded to the current local knowledge base. Cause: The Data Source Filtering Rules were not configured, resulting in recall of external research report data not associated with the current knowledge base.
Phenomenon: In mixed retrieval scenarios, returned citation entries are mixed with research report content from non-plastics and rubber categories. Cause: The Document Classification Tag Filtering rule was not configured, and uploaded research reports were not tagged by category, resulting in inability to accurately filter retrieval results.
Phenomenon: Parsing errors are triggered after embedding Knowledge Base ID or Document Reference Variable in application configuration. Cause: Variable Resolution Priority was not configured correctly, resulting in failure of application-layer variable replacement to be passed to the data source matching logic of the retrieval engine.

How to Confirm Configuration is Correct

Initiate a retrieval targeting a specific plastics and rubber grade (such as LLDPE 7042), check if returned citation entries include matching publishing institutions, publishing times, and core data fields.
Adjust the Similarity Threshold to the 0.7-0.85 range, compare the correlation changes of the two retrieval results to confirm the threshold configuration takes effect.
Test the mixed retrieval scenario, filter by specifying category tags, confirm that returned results only include plastics and rubber related research reports.
Embed document reference variables in the application configuration, initiate a test call, confirm there are no variable parsing errors and citation sources are displayed correctly.

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.