Triple
T27459074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fukoku Tower |
E692681
|
entity |
| Predicate | hasArchitectFirm |
P2468
|
FINISHED |
| Object | Dominique Perrault Architecture |
—
|
NE NERFINISHED |
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: Dominique Perrault Architecture | Statement: [Fukoku Tower, hasArchitectFirm, Dominique Perrault Architecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArchitectFirm Context triple: [Fukoku Tower, hasArchitectFirm, Dominique Perrault Architecture]
-
A.
architectureFirm
chosen
Indicates that one entity is an architecture firm responsible for providing architectural services or design work to another entity.
-
B.
hasArchitecturalFirmNationality
Indicates that an architectural firm is associated with or originates from a specific country or nationality.
-
C.
hasRelationToArchitect
Indicates that one entity has a specified relationship or association with an architect.
-
D.
architectEmployed
Indicates that an architect is employed by a particular organization, firm, or individual.
-
E.
hasArchitecturalDiscipline
Indicates that one entity is associated with, practices, or specializes in a particular architectural discipline or field.
- 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_69ef5207903881909427745cda05d27a |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d26ceb08819091c71c001e954936 |
completed | May 3, 2026, 4:43 a.m. |
Created at: April 27, 2026, 12:49 p.m.