Triple
T10386895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imperial Hotel, Tokyo |
E244784
|
entity |
| Predicate | WrightBuildingDemolished |
P51835
|
FINISHED |
| Object | 1968 |
—
|
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: 1968 | Statement: [Imperial Hotel, Tokyo, WrightBuildingDemolished, 1968]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: WrightBuildingDemolished Context triple: [Imperial Hotel, Tokyo, WrightBuildingDemolished, 1968]
-
A.
demolishedWith
Indicates that one entity was destroyed or torn down using another specified tool, method, or agent.
-
B.
previousBuildingDemolished
chosen
Indicates that a building which previously occupied the same site or fulfilled the same role has been demolished.
-
C.
demolishedOrDestroyed
Indicates that one entity has caused another entity to be torn down, ruined, or rendered unusable, typically through deliberate demolition or destructive force.
-
D.
demolishedAfter
Indicates that one entity was demolished at a point in time later than the demolition of another entity.
-
E.
demolishedOriginalStructures
Indicates that one entity has completely destroyed or removed the original structures associated with another entity.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9a4e6748190bd9dd319de94c659 |
completed | April 7, 2026, 11:25 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb0e7a88190bec0b7a52c70dfe2 |
completed | April 7, 2026, 10:42 a.m. |
Created at: April 6, 2026, 12:05 p.m.