Triple
T21541560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shikinen Sengū |
E531500
|
entity |
| Predicate | effectOnOldStructures |
P141651
|
FINISHED |
| Object | old buildings are dismantled |
—
|
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: old buildings are dismantled | Statement: [Shikinen Sengū, effectOnOldStructures, old buildings are dismantled]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnOldStructures Context triple: [Shikinen Sengū, effectOnOldStructures, old buildings are dismantled]
-
A.
affectedStructure
Indicates that one entity is the structure, component, or part that is impacted, altered, or influenced by another entity or event.
-
B.
remainingStructuresUsedFor
Indicates that the remaining structures of an entity are utilized for a specified purpose or function.
-
C.
demolitionImpact
chosen
Indicates the effect or consequences that a demolition action has on a target entity or its surrounding environment.
-
D.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
E.
replacedStructureDemolished
Indicates that a structure which has been replaced by another has subsequently been demolished.
- 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_69e0c45f17148190949c330ab9c27706 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee9d12b264819096f844b5833198aa |
completed | April 26, 2026, 11:17 p.m. |
| PD | Predicate disambiguation | batch_69e6320766308190ba5dca2f7c826aa4 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:28 p.m.