Triple
T16088719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1992 Windsor Castle fire |
E390301
|
entity |
| Predicate | structuralImpact |
P103390
|
FINISHED |
| Object | significant damage to roofs and floors |
—
|
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: significant damage to roofs and floors | Statement: [1992 Windsor Castle fire, structuralImpact, significant damage to roofs and floors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: structuralImpact Context triple: [1992 Windsor Castle fire, structuralImpact, significant damage to roofs and floors]
-
A.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
B.
structuralIssues
Indicates that there are problems or deficiencies in the design, construction, or integrity of a structure or system.
-
C.
impactDescription
chosen
Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
-
D.
structuralAmbition
Indicates an entity’s intention or effort to change, shape, or influence an existing structure, system, or organizational framework.
-
E.
affectedStructure
Indicates that one entity is the structure, component, or part that is impacted, altered, or influenced by another entity or event.
- 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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff63edb0819092cbb671967bbdcd |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e1827ad7c88190b867da511cbfb7fa |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:59 a.m.