Triple
T27534644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Rose of York flag |
E695063
|
entity |
| Predicate | floralSymbol |
P104578
|
FINISHED |
| Object | white rose |
—
|
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: white rose | Statement: [White Rose of York flag, floralSymbol, white rose]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floralSymbol Context triple: [White Rose of York flag, floralSymbol, white rose]
-
A.
flowerSymbolMeaning
Indicates that a particular flower is used to represent or convey a specific symbolic meaning or message.
-
B.
nationalFlower
Indicates that a particular flower is officially designated as the national flower of a country or region.
-
C.
flowerType
Indicates the specific kind or category of flower associated with an entity.
-
D.
hasMainFloralSymbol
chosen
Indicates that an entity is associated with a primary or most representative floral symbol.
-
E.
hasBirthFlower
Indicates that one entity is the designated birth flower associated with another entity (typically a person or birth date).
- 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_69ef538608b081908b9f659bb09d5e0f |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f62f5996508190894a769a5199945d |
completed | May 2, 2026, 5:07 p.m. |
| PD | Predicate disambiguation | batch_69f623ac3a9c8190a6ee0c137b09e4b0 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 1:28 p.m.