Triple
T30787316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cathedral of the Immaculate Conception, Beijing |
E783988
|
entity |
| Predicate | facedDestructionBy |
P5325
|
FINISHED |
| Object | fires |
—
|
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: fires | Statement: [Cathedral of the Immaculate Conception, Beijing, facedDestructionBy, fires]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: facedDestructionBy Context triple: [Cathedral of the Immaculate Conception, Beijing, facedDestructionBy, fires]
-
A.
sufferedDestructionOf
Indicates that one entity experienced damage, ruin, or loss as a result of the destruction of another entity.
-
B.
sufferedDestructionIn
Indicates that an entity experienced damage, ruin, or devastation during or as part of a specified event or period.
-
C.
hasCauseOfDestruction
chosen
Indicates that one entity is the cause or agent responsible for the destruction or damage of another entity.
-
D.
hasDemolitionOrDestruction
Indicates that one entity causes, undergoes, or is associated with the demolition or destruction of another entity.
-
E.
demolishedAsResultOf
Indicates that one entity was demolished as a direct consequence or outcome of another event, action, or condition.
- 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_69f224b213c8819083886073f90b647e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6900ab06c8190856785240a8faa83 |
completed | May 3, 2026, midnight |
| PD | Predicate disambiguation | batch_69f68b7b03488190b1db5fde4c7dd6e5 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:41 p.m.