Triple
T18595137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acinonyx |
E454473
|
entity |
| Predicate | hasLivingSpecies |
P21216
|
FINISHED |
| Object | Acinonyx jubatus |
—
|
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: Acinonyx jubatus | Statement: [Acinonyx, hasLivingSpecies, Acinonyx jubatus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Acinonyx jubatus Context triple: [Acinonyx, hasLivingSpecies, Acinonyx jubatus]
-
A.
Acinonyx
Acinonyx is a genus of felids best known for the cheetah, a highly specialized, fast-running big cat.
-
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.
Cheetah
Cheetah is the internal codename for Mac OS X 10.0, the first major release of Apple's Mac OS X operating system.
-
D.
Cheetah
chosen
The cheetah is the world’s fastest land animal, a slender, spotted big cat renowned for its incredible acceleration and high-speed chases across open grasslands.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e545ba3bc881908f5308e09d54e05b |
completed | April 19, 2026, 9:14 p.m. |
Created at: April 10, 2026, 11:44 a.m.