Triple
T15186677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuno National Park |
E362893
|
entity |
| Predicate | firstCheetahReleaseYear |
P78514
|
FINISHED |
| Object | 2022 |
—
|
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: 2022 | Statement: [Kuno National Park, firstCheetahReleaseYear, 2022]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstCheetahReleaseYear Context triple: [Kuno National Park, firstCheetahReleaseYear, 2022]
-
A.
firstDeployedIn
Indicates the time or place where something (such as a system, product, or technology) was initially put into operational use or service.
-
B.
firstModelIntroduced
Indicates that one entity is the earliest or original model introduced in relation to another entity or context.
-
C.
firstDeployedAt
Indicates the date and time when an entity was initially put into use or made operational.
-
D.
firstPrototypeYear
Indicates the year in which the first prototype of an entity was created or completed.
-
E.
firstCaptureYear
chosen
Indicates the year in which an entity was first captured or recorded as captured.
- 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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0067995fc8190b048f15086bd42f0 |
completed | April 15, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69deb97bd8bc8190b2ad4888f97cf963 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:09 a.m.