Triple
T10047698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Candice Swanepoel |
E207658
|
entity |
| Predicate | discoveredAsModelIn |
P33675
|
FINISHED |
| Object | flea market |
—
|
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: flea market | Statement: [Candice Swanepoel, discoveredAsModelIn, flea market]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: discoveredAsModelIn Context triple: [Candice Swanepoel, discoveredAsModelIn, flea market]
-
A.
discoveredAsPartOf
Indicates that something was found, identified, or revealed in the course of a larger activity, process, or investigation of which it formed a component.
-
B.
introducedAsModel
chosen
Indicates that one entity is presented or identified to others in the role or capacity of a model.
-
C.
isModelOf
Indicates that one entity serves as a representation or abstraction that captures the structure or behavior of another entity.
-
D.
discoveredAs
Indicates that one entity was first identified, found, or recognized in the role or form specified by another entity.
-
E.
discoveredWith
Indicates that one entity was found, detected, or identified using another entity as the means, tool, method, or accompanying context of discovery.
- 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_69ca835ad0608190b7c80b292da004f5 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcf664dd881908786fcd802bf10da |
completed | April 2, 2026, 2:07 a.m. |
| PD | Predicate disambiguation | batch_69cd4b8d2280819089de27e57babd1f3 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 8:56 p.m.