Triple
T29390829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regular Category (World Robot Olympiad) |
E745364
|
entity |
| Predicate | usesRobotType |
P35727
|
FINISHED |
| Object | wheeled mobile robots |
—
|
LITERAL FINISHED |
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: wheeled mobile robots | Statement: [Regular Category (World Robot Olympiad), usesRobotType, wheeled mobile robots]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesRobotType Context triple: [Regular Category (World Robot Olympiad), usesRobotType, wheeled mobile robots]
-
A.
hasRobot
Indicates that one entity possesses, controls, or is associated with a robot.
-
B.
isRobotic
Indicates that an entity is robotic, meaning it is a robot or operates using robotic mechanisms or technology.
-
C.
robotType
chosen
Indicates the specific category or kind of robot that an entity belongs to.
-
D.
isFullyRobotic
Indicates that the entity operates entirely through robotic mechanisms without human biological components or manual control.
-
E.
hasOnboardRobot
Indicates that one entity (typically a vehicle, device, or platform) is equipped with or carries a robot on board.
- 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_69f0a79dfabc81908755382ee47791e2 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f697eabb048190bc01a830f14942c6 |
completed | May 3, 2026, 12:33 a.m. |
| PD | Predicate disambiguation | batch_69f69664142c8190bc695501056b0236 |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 28, 2026, 2:42 p.m.