Triple
T4830411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vase with Fifteen Sunflowers |
E107930
|
entity |
| Predicate | numberOfSunflowersDepicted |
P59913
|
FINISHED |
| Object | 15 |
—
|
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: 15 | Statement: [Vase with Fifteen Sunflowers, numberOfSunflowersDepicted, 15]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSunflowersDepicted Context triple: [Vase with Fifteen Sunflowers, numberOfSunflowersDepicted, 15]
-
A.
petalCount
Indicates the number of petals associated with an entity, typically a flower or floral structure.
-
B.
numberOfFiguresDepicted
Indicates the total count of distinct figures shown within a given depiction or representation.
-
C.
numberOfMandalas
Indicates the quantity or count of mandalas associated with a given entity.
-
D.
numberOfRoseVarieties
Indicates the quantitative count of distinct rose varieties associated with an entity.
-
E.
hasFlowerColor
Indicates that an entity (typically a plant or flower) possesses a specific flower color.
- 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_69bd43fac8188190803f0327190621e4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1fe130819087ae01309f96a0c8 |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6dda5e808190a26ec85e4499d8e4 |
completed | March 20, 2026, 3:55 p.m. |
Created at: March 20, 2026, 1:24 p.m.