Triple
T1173483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emblem of South Korea |
E24964
|
entity |
| Predicate | petalsRepresent |
P24024
|
FINISHED |
| Object | prosperity |
—
|
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: prosperity | Statement: [Emblem of South Korea, petalsRepresent, prosperity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: petalsRepresent Context triple: [Emblem of South Korea, petalsRepresent, prosperity]
-
A.
petalCount
Indicates the number of petals associated with an entity, typically a flower or floral structure.
-
B.
petalMarkings
Indicates the pattern, color, or distinctive markings present on the petals of a flower in relation to the flower they belong to.
-
C.
petalTexture
Indicates the type or quality of surface texture exhibited by a flower’s petals.
-
D.
flowerSymbolMeaning
chosen
Indicates that a particular flower is used to represent or convey a specific symbolic meaning or message.
-
E.
flowerStructure
Indicates the structural characteristics or organization of a flower, such as the arrangement and form of its parts.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd53e4b48190abb2167f8074a6bc |
completed | March 1, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5844348190b01ac6506906ba3b |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.