Triple
T13543066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyalami Grand Prix Circuit |
E323438
|
entity |
| Predicate | hasCorner |
P42380
|
FINISHED |
| Object | Cheetah |
E801805
|
NE 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: Cheetah | Statement: [Kyalami Grand Prix Circuit, hasCorner, Cheetah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cheetah Context triple: [Kyalami Grand Prix Circuit, hasCorner, Cheetah]
-
A.
Cheetah
Cheetah is the internal codename for Mac OS X 10.0, the first major release of Apple's Mac OS X operating system.
-
B.
Cheetah
Cheetah is a classic DC Comics supervillain and archenemy of Wonder Woman, often depicted as a woman cursed or empowered with the speed, ferocity, and appearance of a cheetah.
-
C.
Gepard
The Gepard is a German self-propelled anti-aircraft gun system featuring twin 35 mm cannons and radar for tracking and engaging low-flying aircraft and drones.
-
D.
Atlas Cheetah
chosen
The Atlas Cheetah is a South African modernized variant of the Dassault Mirage III fighter aircraft, upgraded with advanced avionics and improved combat capabilities.
-
E.
Gazelle
The Gazelle is a light, fast, and highly maneuverable French-designed military helicopter widely used for reconnaissance, light attack, and training missions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d8076776248190bdf0d4fa1f85a5fc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafda36248190acabde65a88c5471 |
completed | April 12, 2026, 2:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75da094288190aff108b006c3da1f |
completed | May 3, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:45 p.m.