Triple
T9144788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tulip Festival in Albany |
E219423
|
entity |
| Predicate | approximateNumberOfTulips |
P87018
|
FINISHED |
| Object | thousands of tulips |
—
|
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: thousands of tulips | Statement: [Tulip Festival in Albany, approximateNumberOfTulips, thousands of tulips]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfTulips Context triple: [Tulip Festival in Albany, approximateNumberOfTulips, thousands of tulips]
-
A.
numberOfFlowersDepicted
Indicates the quantity of flowers shown or represented in an image or depiction.
-
B.
petalCount
Indicates the number of petals associated with an entity, typically a flower or floral structure.
-
C.
numberOfPlants
Indicates the total count of plants associated with a given entity or context.
-
D.
numberOfSunflowersDepicted
Indicates the count of sunflower instances shown within a given depiction or representation.
-
E.
hasApproximateNumberOfVarieties
Indicates that an entity is associated with an estimated or non-exact count of different varieties or types.
- 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_69ca83e121dc81909912bd66953081c5 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca9166d308190a742ae68371439ee |
completed | April 1, 2026, 5:11 a.m. |
| PD | Predicate disambiguation | batch_69cc6603ce8c8190bf6e8d6754bdec54 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc6a3d230881909635b2ccea35cedb |
completed | April 1, 2026, 12:43 a.m. |
Created at: March 30, 2026, 7:19 p.m.