Triple
T7034413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Region of Kainuu |
E163343
|
entity |
| Predicate | hasRegionalFlower |
P74596
|
FINISHED |
| Object | twinflower |
—
|
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: twinflower | Statement: [Region of Kainuu, hasRegionalFlower, twinflower]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionalFlower Context triple: [Region of Kainuu, hasRegionalFlower, twinflower]
-
A.
hasPrefecturalFlower
Indicates that a particular prefecture is associated with a designated official flower.
-
B.
nationalFlower
Indicates that a particular flower is officially designated as the national flower of a country or region.
-
C.
hasOfficialStateFlower
Indicates that a political entity is formally designated as having a particular flower as its official state symbol.
-
D.
stateFlower
Indicates the official flower designated as the symbolic floral emblem of a particular state.
-
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. 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_69c6885d691c81908cf7d31083113886 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e458ad9c81908c3f492b317ce291 |
completed | March 27, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69c6e1b9a2488190aea351d96afa5a12 |
completed | March 27, 2026, 7:59 p.m. |
| PDg | Predicate description generation | batch_69c6e456e89481908df42a1b4232a4a0 |
completed | March 27, 2026, 8:11 p.m. |
Created at: March 27, 2026, 2:36 p.m.