Document Parsing and Chunking for Training Provider Scheduling and Lesson Records: Compare Documents and Locate Differences

Training Schedules: review parsing for document checks. Compare the source records, required inputs and downstream results before handing the task over.

What this category's data looks like

In the scheduling and class-hour consumption scenario of training institutions, materials mainly come from three types of documents: class schedules, class-hour consumption records, and schedule change requests. The update rhythm accumulates daily with scheduling adjustments, class-hour consumption, and temporary schedule changes. Field characteristics center on course name, student name, class-hour quantity, class date, signature, and receipt. When a class schedule enters this function, it serves as the baseline material, class-hour consumption records serve as the actual consumption material, and schedule change requests serve as the change material. The three types of materials each assume a comparison role, making it convenient to verify on the same object whether the name, quantity, and date are consistent, and to locate discrepancy fields.

Configuration and implementation checks

Parsing and training tasks (server-side tasks) only output data rows and index status (parsed, indexing, indexed). The discrepancy list must be handled next by retrieval and subsequent processing. After material parsing and chunking are completed, they are immediately persisted as visible data rows and bound to a unique data identifier. The index transitions through three states, and data pending indexing does not participate in recall.

ObjectCheckVerification action
Class scheduleCourse name, class-hour quantity, class date, and signature fields are consistent in both materialsVerify the file record and the data row separately, check whether the data row status is parsed / indexing / indexed, and inspect the chunking results corresponding to chunkSize and chunkSplitter
Class-hour consumption recordThe name, quantity, and date of the same record are consistent with the ledgerOpen the data row to verify its status, confirm that data pending indexing is not recalled, and verify the processing mode corresponding to trainingType
Schedule change requestThe change date and signature receipt are complete and the version is synchronizedInspect the data rows covered by the rebuild task, and confirm that only data with completed indexing is covered
File and data row identifiersThe identities of the file record and the data row are distinguishableVerify the file record and the data row separately, and confirm that the unique data identifier is bound correctly

Three common errors

  • Symptom: The name, quantity, or date of the same record does not match between the class schedule and the class-hour consumption record. Cause: The material sources are not synchronized, and the fields are not aligned to the same object.
  • Symptom: The schedule change request lacks a signature or receipt, and the discrepancy list cannot be closed. Cause: The change material is not synchronized with the version, and the review lacks a basis.
  • Symptom: Newly uploaded materials cannot be found. Cause: The data row is in a pending-indexing state, and the retrieval layer naturally isolates it from recall.

How to verify the setup

Acceptance for this function: Upload one material, observe the data row status transitions and the coverage scope of the rebuild task, confirm that the status is parsed / indexing / indexed, and verify the chunking and processing modes corresponding to chunkSize, chunkSplitter, and trainingType.

Business test: Use one real record to find a field inconsistent with the ledger, hand it to the reviewer for confirmation, and write it back.

  • Open the data row to verify its status, confirm that it is consistent with the interface display, and verify the file record and the data row separately.
  • Inspect the data rows covered by the rebuild task, and confirm that only data with completed indexing is covered.