introvoyz041/FactoryBench_Generation huggingface dataset:
Question type: predictive
Question template: The robot is performing a {task} task. We want to isolate the {phase} in the robot's time series. Assuming a fixed window length of {window_length} timesteps, at which timestamp should the window begin? Answer only with an integer or decimal number, nothing else.
Answer format: numerical
Notes: Ground truth is trivially generated by segmenting different phases from the raw data. Accept answers within a tolerance band.
Question type: anomaly detection
Question template: What anomaly are present in the following time series? Answer only with a letter indicate your answer (ie. A, B, C or D). Do not output anything else.
Answer format: single_choice_multi_select
Number of choices: 4
Notes: Ground truth is directly available from labeled data. Include the true anomaly/anomalies, at least one plausible distractor, and a 'no anomaly present' option.
Question type: comparative
Question template: What changed between the two instances of robotic time series data?  Answer only with a 4 letter string using F and T to indicate your answers (ie. TFFT to indicate True, False, False, True). Do not output anything else.
Hidden metadata: robot, gripper
Answer format: multiple_choice_multi_select
Number of choices: 4
Notes: Options include: robot, mounting configuration (e.g., inverted or repositioned), task, presence of a specific anomaly. Ground truth is generated from instance metadata. Easily scalable.
Question type: comparative
Question template: Rank the following robot time series segments from most to least severe anomaly. Answer only with a four letter string indicating your ranking (ie. DCAB), nothing else.
Answer format: ranking
Number of items: 4
Notes: Ground truth is straightforward given anomaly metadata (e.g., fault severity labels). Consider restricting context to a feature subset (e.g., joint currents only) to keep query length manageable. Model must output a permutation of [A, B, C, D].
Question type: identification
Question template: What robot does this sensor data originate from? Answer only with the letter of the correct option (ie. A), nothing else.
Hidden metadata: robot, gripper
Answer format: multiple_choice_single_select
Number of choices: 3
Notes: Ground truth is derived from episode metadata (robot_model / machine_id). The model must infer the robot from signal characteristics like joint count, torque profiles, and kinematic signatures.