Triple
T33280751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1992 Los Angeles riots |
E852035
|
entity |
| Predicate | numberOfFires |
—
|
GENERATED |
| Object | over 1000 |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFires Context triple: [1992 Los Angeles riots, numberOfFires, over 1000]
-
A.
numberOfFirefightersInvolved
Indicates the total count of firefighters who participated in or were involved in a specific event, incident, or operation.
-
B.
notableFire
Indicates that a significant or historically important fire event is associated with the subject.
-
C.
fireType
Indicates that one entity has a specific classification or category related to fire (e.g., type, kind, or nature of fire).
-
D.
fireOccurred
Indicates that a fire event took place at a specific time and/or location.
-
E.
fires
Indicates that an agent initiates the discharge or ignition of something, such as a weapon, engine, or explosive device, causing it to operate or go off.
- F. None of above. chosen
Provenance (1 batch)
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_69f349653da08190819876015a298fdb |
completed | April 30, 2026, 12:21 p.m. |
Created at: May 1, 2026, 1:32 a.m.