Triple
T28930666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holland Park School |
E733768
|
entity |
| Predicate | hasPreviousBuildingDemolished |
P51835
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Holland Park School, hasPreviousBuildingDemolished, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPreviousBuildingDemolished Context triple: [Holland Park School, hasPreviousBuildingDemolished, yes]
-
A.
previousBuildingDemolished
chosen
Indicates that a building which previously occupied the same site or fulfilled the same role has been demolished.
-
B.
hasFormerBuilding
Indicates that an entity previously occupied or used a different building, which is identified as its former building.
-
C.
demolishedAfter
Indicates that one entity was demolished at a point in time later than the demolition of another entity.
-
D.
demolishedOrRedeveloped
Indicates that one entity has been torn down, replaced, or substantially rebuilt or repurposed into another entity.
-
E.
demolishedOrDestroyed
Indicates that one entity has caused another entity to be torn down, ruined, or rendered unusable, typically through deliberate demolition or destructive force.
- 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_69f05b0b49b08190b8994b339c7980f6 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69ff289541e0819096eeceb8e6332650 |
completed | May 9, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69ff281ab1988190920f0443be9f10cc |
completed | May 9, 2026, 12:27 p.m. |
Created at: April 28, 2026, 8:27 a.m.