Triple
T21587507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bagatelle rose garden |
E532688
|
entity |
| Predicate | numberOfVarieties |
P49018
|
FINISHED |
| Object | thousands of rose varieties |
—
|
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 rose varieties | Statement: [Bagatelle rose garden, numberOfVarieties, thousands of rose varieties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfVarieties Context triple: [Bagatelle rose garden, numberOfVarieties, thousands of rose varieties]
-
A.
hasApproximateNumberOfVarieties
chosen
Indicates that an entity is associated with an estimated or non-exact count of different varieties or types.
-
B.
numberOfPrimaryVarieties
Indicates the count of distinct primary varieties associated with a given entity.
-
C.
has32Varieties
Indicates that one entity possesses or includes exactly 32 distinct types, forms, or varieties of another entity.
-
D.
hasVarietyOf
Indicates that an entity possesses or offers multiple different types, forms, or versions of something.
-
E.
hasNonStandardizedVarieties
Indicates that an entity possesses forms or variants that are not governed by a uniform or officially established standard.
- 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_69e0c46251648190876f0427cf2d321b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eeeb621ab88190a33a943424ffb306 |
completed | April 27, 2026, 4:51 a.m. |
| PD | Predicate disambiguation | batch_69e632109d048190b4ac3f14fe48d1a0 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:31 p.m.