Triple
T20350482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Game Boy Camera |
E495991
|
entity |
| Predicate | cameraRotation |
P60184
|
FINISHED |
| Object | approximately 180 degrees |
—
|
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: approximately 180 degrees | Statement: [Game Boy Camera, cameraRotation, approximately 180 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cameraRotation Context triple: [Game Boy Camera, cameraRotation, approximately 180 degrees]
-
A.
cropRotationPractice
Indicates that an entity engages in the planned sequence of growing different crops on the same land over time to manage soil health, pests, and productivity.
-
B.
rotationAxis
chosen
Indicates the axis around which an object or system rotates or is intended to rotate.
-
C.
arenaRotationChange
Indicates a change in the orientation or rotational state of an arena relative to its previous position.
-
D.
rotationEffect
Indicates that one entity is rotated around a specified point or axis by a given angle, affecting its orientation relative to other entities.
-
E.
cameraSystem
Indicates a relationship where an entity functions as or is part of a camera-based monitoring or imaging system.
- 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_69e0b4a3320881909495ae8bc30bc2dc |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6784f8ff48190a070888786f6a989 |
completed | April 20, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_69e57636b4808190bc2855af48a3ccdc |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:24 a.m.