Triple
T37225267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jane Jetson |
E922988
|
entity |
| Predicate | hasRobotAssistant |
P69372
|
FINISHED |
| Object | Rosie the Robot |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Rosie the Robot | Statement: [Jane Jetson, hasRobotAssistant, Rosie the Robot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRobotAssistant Context triple: [Jane Jetson, hasRobotAssistant, Rosie the Robot]
-
A.
hasRobot
chosen
Indicates that one entity possesses, controls, or is associated with a robot.
-
B.
hasOnboardRobot
Indicates that one entity (typically a vehicle, device, or platform) is equipped with or carries a robot on board.
-
C.
isRobotic
Indicates that an entity is robotic, meaning it is a robot or operates using robotic mechanisms or technology.
-
D.
isFullyRobotic
Indicates that the entity operates entirely through robotic mechanisms without human biological components or manual control.
-
E.
hasRobotCharacterRole
Indicates that an entity participates in a role or function specifically as a robot character within a given context or work.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76ea7f0008190b31b8e30f3d05a71 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fed83b1d188190a318b0ad3003200a |
completed | May 9, 2026, 6:46 a.m. |
| PD | Predicate disambiguation | batch_69fed78e03548190b6e6ad93ae8d131d |
completed | May 9, 2026, 6:43 a.m. |
Created at: May 3, 2026, 4:15 p.m.