Triple
T7891451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azuchi Castle ruins |
E183243
|
entity |
| Predicate | originalStructureDemolished |
P74976
|
FINISHED |
| Object | 1582 |
—
|
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: 1582 | Statement: [Azuchi Castle ruins, originalStructureDemolished, 1582]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalStructureDemolished Context triple: [Azuchi Castle ruins, originalStructureDemolished, 1582]
-
A.
originalConstructionDestroyed
Indicates that the initially built or first version of an object, structure, or work has been destroyed or no longer exists in its original form.
-
B.
demolishedOriginalStructures
Indicates that one entity has completely destroyed or removed the original structures associated with another entity.
-
C.
mostStructuresDemolished
Indicates that the subject is the entity responsible for demolishing the greatest number of structures within a given context or set.
-
D.
hasDemolitionOrDestruction
Indicates that one entity causes, undergoes, or is associated with the demolition or destruction of another entity.
-
E.
originalStructureDemolishedYear
chosen
Indicates the year in which the original structure associated with the subject was 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_69ca828c474c8190a254d6499871eaff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39ee137081908e87e35016c3a176 |
completed | March 31, 2026, 3:05 a.m. |
| PD | Predicate disambiguation | batch_69cae92b0cd881908e715a10d3252e83 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5 p.m.