Triple
T25639850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canadian Tulip Festival |
E642807
|
entity |
| Predicate | approximateTulipCount |
P87018
|
FINISHED |
| Object | over one million 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: over one million tulips | Statement: [Canadian Tulip Festival, approximateTulipCount, over one million tulips]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateTulipCount Context triple: [Canadian Tulip Festival, approximateTulipCount, over one million tulips]
-
A.
approximateNumberOfTulips
chosen
Indicates that the relationship specifies an estimated or approximate count of tulips associated with an entity.
-
B.
numberOfFlowersDepicted
Indicates the quantity of flowers shown or represented in an image or depiction.
-
C.
numberOfPlants
Indicates the total count of plants associated with a given entity or context.
-
D.
petalCount
Indicates the number of petals associated with an entity, typically a flower or floral structure.
-
E.
numberOfTrees
Indicates the count or quantity of trees associated with a given entity or context.
- 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_69e77e7ce28081908b08d65ee6e5c8be |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f67f0488bc819089fbd2d2478158d3 |
completed | May 2, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f67e3ed894819094c067c1ef624951 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 21, 2026, 5:39 p.m.