Questions about a recurring person in long videos are rarely answered from a single moment. They require evidence that is sufficient for the claim, comparisons across episodes, synthesis over recurring audiovisual patterns, and refusal when the source material does not support an answer. Existing long-video benchmarks do not isolate these requirements. We introduce KnowMeBenchV2, an evaluation-only benchmark over five public multi-episode video series, with 327 videos and 3,061 questions covering four evidence scopes: single-clip extraction, temporal and event relations, cross-episode ordering, and cross-episode persona synthesis. A separate grounded-abstention task serves as a contrastive support check: its questions are surface-similar to supported person-linked questions but are not licensed by the source evidence. The most interpretive synthesis items are human-authored and quality-audited by trained annotators with full source access. A matched human reference reaches 78.0 on cross-episode synthesis. To diagnose failures, we compare evidence routes under a fixed Qwen3.5-9B answerer and a task-matched pre-tokenization character routing budget. ASR-Retrieval reaches 2.7 on synthesis, while KnowMe reaches 64.9. In this diagnostic, the final answerer reasons over textualized evidence constructed from audiovisual sources rather than raw video tokens. The gap therefore isolates the importance of audiovisual evidence construction and cross-episode organization before answer generation.