Triple
T19175561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camp Fire |
E469427
|
entity |
| Predicate | destroyedHomes |
P1583
|
FINISHED |
| Object | over 13,000 residences |
—
|
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: over 13,000 residences | Statement: [Camp Fire, destroyedHomes, over 13,000 residences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: destroyedHomes Context triple: [Camp Fire, destroyedHomes, over 13,000 residences]
-
A.
buildingsDestroyed
chosen
Indicates that one or more buildings have been damaged to the point of destruction as a result of some event or action.
-
B.
demolishedOrDestroyed
Indicates that one entity has caused another entity to be torn down, ruined, or rendered unusable, typically through deliberate demolition or destructive force.
-
C.
destroyedCity
Indicates that an entity has caused the complete or near-complete destruction of a city.
-
D.
numberOfBusinessesDestroyed
Indicates the quantity of businesses that have been destroyed in a given event or context.
-
E.
sufferedDestructionOf
Indicates that one entity experienced damage, ruin, or loss as a result of the destruction of 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_69d8dd09d5a081909ae43c286651ae5a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f166d3888190adaf6dc8531a8ed1 |
completed | April 20, 2026, 9:27 a.m. |
| PD | Predicate disambiguation | batch_69e4b9bb158481909478ca2e06f3ba39 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:06 p.m.