Triple
T16088691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1992 Windsor Castle fire |
E390301
|
entity |
| Predicate | damagedArea |
P1586
|
FINISHED |
| Object | approximately 115 rooms |
—
|
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: approximately 115 rooms | Statement: [1992 Windsor Castle fire, damagedArea, approximately 115 rooms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: damagedArea Context triple: [1992 Windsor Castle fire, damagedArea, approximately 115 rooms]
-
A.
damagedIn
Indicates that an entity has suffered harm, impairment, or destruction as a result of a specified event, process, or condition.
-
B.
affectedArea
chosen
Indicates the specific region or extent over which an event, condition, or influence has an impact.
-
C.
areaDestroyed
Indicates that a specified portion or region has been damaged or ruined to the point of destruction.
-
D.
damagedBy
Indicates that one entity has caused harm, impairment, or deterioration to another entity.
-
E.
damageTo
Indicates a relationship where one entity causes harm, loss, or deterioration to 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_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.