Q16 of 60 — CCA Practice Exam

Structured Data Extraction

Your structured data extraction pipeline processes a corpus of 50,000 legal contracts in long-running agent sessions, with Claude extracting clause types, party names, and obligation dates per document. Operators report that sessions processing the final 20% of documents exhibit a sharp increase in truncated extractions — partial JSON records, missing fields, and mid-document cutoffs — despite no changes to prompts or schemas. Logs show these failures cluster in sessions that have already processed thousands of documents. What is the most likely root cause?

A. The extraction schema's required fields create token overhead that compounds across documents, eventually exceeding the per-call output limit.

B. Sessions lacking context awareness cause Claude to continue processing as if full capacity remains, leading to abrupt truncation when the context window is exhausted near its boundary.

C. The legal documents in the final 20% are structurally more complex, requiring more tokens per extraction and causing the model to exceed its response budget.

D. The pipeline's tool call loop accumulates system_warning messages in the conversation history, diluting attention on the extraction schema by the late-session documents.