Triple
T18875393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yaya DaCosta |
E461669
|
entity |
| Predicate | realityShowPlacement |
P133294
|
FINISHED |
| Object | runner-up on America's Next Top Model, Cycle 3 |
—
|
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: runner-up on America's Next Top Model, Cycle 3 | Statement: [Yaya DaCosta, realityShowPlacement, runner-up on America's Next Top Model, Cycle 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: realityShowPlacement Context triple: [Yaya DaCosta, realityShowPlacement, runner-up on America's Next Top Model, Cycle 3]
-
A.
networkOfRealityShow
Indicates that a particular reality show is broadcast or produced by a specific television network.
-
B.
typicalLivePlacement
Indicates the usual or most common location or environment in which an entity is typically found living or situated.
-
C.
hasRealityTVElement
Indicates that something includes characteristics, themes, or stylistic features commonly associated with reality television.
-
D.
hasRealityTVSeries
Indicates that an entity is the subject or focus of a reality television series.
-
E.
settingWithinShow
Indicates that one setting (such as a location or environment) exists as part of, or is contained within, a particular show.
- F. None of above. chosen
Provenance (4 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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c3ce07788190a179705eb1b6c824 |
completed | April 20, 2026, 6:12 a.m. |
| PD | Predicate disambiguation | batch_69e48d22dde8819093b1d963bd673365 |
completed | April 19, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e49785fd7081909577e90a55df0a35 |
completed | April 19, 2026, 8:51 a.m. |
Created at: April 10, 2026, 11:57 a.m.