Triple
T6721476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The City of the Red Flamboyant |
E153405
|
entity |
| Predicate | hasFloralReference |
P68196
|
FINISHED |
| Object | flamboyant tree |
—
|
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: flamboyant tree | Statement: [The City of the Red Flamboyant, hasFloralReference, flamboyant tree]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFloralReference Context triple: [The City of the Red Flamboyant, hasFloralReference, flamboyant tree]
-
A.
hasFloralFeature
chosen
Indicates that an entity possesses a specific floral characteristic, structure, or attribute.
-
B.
hasFlowerColor
Indicates that an entity (typically a plant or flower) possesses a specific flower color.
-
C.
hasBirthFlower
Indicates that one entity is the designated birth flower associated with another entity (typically a person or birth date).
-
D.
floweringUse
Indicates the use or application of something specifically for flowering or promoting the flowering process.
-
E.
numberOfFlowersDepicted
Indicates the quantity of flowers shown or represented in an image or depiction.
- 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_69c6880afb988190ad88011b48ecfcba |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d13861a08190ad19a16dcd76c908 |
completed | March 27, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69c6d08c5d348190a29dee668c398e70 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:07 p.m.