Knowledge Base Retrieval and Recall for Logistics

What data looks like for this category

Intelligent due diligence reports for logistics carriers in the financial sector draw data from carrier qualification documents, annual transportation assessment reports, in-transit monitoring logs, customs clearance documents, signed receipt scans, and similar sources. Three update frequency tiers are used: real-time for in-transit data, daily for monthly waybill archiving, and quarterly for annual carrier assessments. Most documents are in PDF format, containing long text passages and structured tables. Individual reports can span thousands of pages, with fields including waybill number, cargo weight, transportation mileage, and more. Units include kilograms, tons, and kilometers. Some documents have mixed Chinese and English fields, and also include image attachments such as cargo packaging and signed receipt vouchers.

What constraints these characteristics impose on knowledge base retrieval and recall

The high share of long text and thousand-page documents requires chunking strategies that preserve sufficient contextual connections, to avoid splitting critical information. Structured fields and multi-unit fields coexist, so mixed retrieval rules and unit calibration logic must be configured to prevent matching failures caused by unit differences. The high share of image attachments requires enabling OCR to extract text indexes from images; without this, retrieval association for image content is not possible. Wide gaps between update frequencies require setting differentiated incremental update cycles to balance retrieval timeliness and system load. Large individual document sizes require adjusting parsing and chunking timeout thresholds to avoid parsing failures for long documents.

How to set configurations

Configuration Item	Recommended Value Range	Rationale
`maxChunkSize`	800–1200 characters	Logistics due diligence reports mostly consist of long-text waybills and annual assessment documents. The 800–1200 character range retains contextual connections while avoiding overly long chunks that impair retrieval accuracy
`chunkOverlap`	150–200 characters	Retaining leading and trailing overlap after chunking long documents prevents critical waybill fields and carrier qualification information from being split across two chunks, ensuring retrieval continuity
`similarityThreshold`	0.72–0.85	Logistics data mostly relies on structured field matching. A threshold that is too low introduces irrelevant carrier qualification documents, while a threshold that is too high misses valid waybill information
`recallTopK`	Top 8–12 results	A single due diligence review needs to cover multiple carriers and multiple batches of waybills. The 8–12 result range covers core related data while avoiding redundant results
`imageOcrEnable`	Enabled	Logistics documents include image content such as signed receipts and packaging photos. OCR extracts core text from images including waybill numbers and signing information
`incrementalUpdateInterval`	Every 6 hours	In-transit data updates in real time, while waybill data is archived daily. A 6-hour incremental update cycle balances retrieval timeliness and system load

The parameter values provided on this page are common starting points for configuration setup. 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.

Three common mistakes

Issue: Signed receipt images in uploaded logistics documents cannot be properly recalled during retrieval, and the page displays blank content. Cause: The imageOcrEnable configuration is not enabled. Only the original image files are stored without extracting text indexes from the images, so the retrieval system cannot associate waybill information in the images.
Issue: The system returns a parsing timeout error when importing annual assessment reports longer than 500 pages. Cause: The maxChunkSize parameter is not adjusted to a reasonable range. Overly long single chunks exceed parsing thresholds, causing timeouts during the chunking process.
Issue: Both old and new versions of qualification documents for the same carrier appear in retrieval results. Cause: No document version verification rules are configured. Incremental updates only append new documents without deleting old versions, resulting in both old and new documents being recalled.

How to confirm configurations are set correctly

Upload a test document that includes signed receipt images and structured waybill tables, check if the parsed text blocks include waybill numbers and signing date information from the images, to confirm the OCR configuration is active.
Import a 1000-page annual logistics assessment report, check if the total number of chunks after processing matches expectations, and no individual chunk exceeds the maxChunkSize setting.
Enter a search term that includes a specific carrier name and transportation mileage, check if the number of returned results falls within the recallTopK range, and the similarity scores meet the similarityThreshold requirements.
Upload an updated carrier qualification document, wait for the period set by incrementalUpdateInterval, then search for the carrier name, confirm only the latest version of the document is returned.

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.