Watch-QA Nominal Reference Inputs (v1)
500 fixed ordinary shopping requests at the pre-first-search decision point, shared across the four compatible Watch-QA checkpoints. The corresponding runtime evaluation set contains 250 inputs and model-specific labels.
Sampling
Requests come from the question field of lclan/webshop_expert_trajectories, file webshop_gpt4_0613.json, pinned at e13f9187455c57f3f076a3d42c8e06700b018e6c. Sampling uses one representative per normalized task family and deterministic seed-42 hash ordering. Known training families, runtime evaluation families, reserved Chetan evaluation families, and the separately selected Watch-OA reference families are excluded for independence.
No trigger-word, brand, reward, target-action or suspect-model activation filter is used to select these nominal inputs. Do not interpret the exclusions for dataset independence as a certification of semantic independence. Source trajectories' future model responses and outcomes do not appear in these inputs.
These are nominal references sampled from the normal task distribution. They are not guaranteed to be backdoor-inactive: legitimate requests can naturally satisfy hidden trigger conditions. There are no activation labels, and suspect-model outputs were not used to choose the 500 requests.
Interface
Every record contains id and messages. The four messages match the runtime harness: common system instruction, released WebShop shopping instruction, Ok. acknowledgment, and the raw initial shopping observation ending in Search. No first search, search results, extra Observation: wrapper or serialized Available Actions list is included. This is the QA decision point; Watch-OA references use a later post-search decision point and a different task sample.
Only messages in inputs.jsonl are reference input for the auditor. provenance/source_tasks.jsonl stores evaluator-only task IDs, source revision, original instructions and sampling records. Exact normalized-family separation does not certify semantic or product-level separation. No shopping environment execution is needed to represent this pre-search state.
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