Triple
T35412190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Riverfront Coliseum |
E1023540
|
entity |
| Predicate | numberOfDeathsIn1979Incident |
—
|
GENERATED |
| Object | 11 |
—
|
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: numberOfDeathsIn1979Incident Context triple: [Riverfront Coliseum, numberOfDeathsIn1979Incident, 11]
-
A.
numberOfDeathsInNotableEvent
chosen
Indicates the total count of deaths that occurred as a result of a specified notable event.
-
B.
numberOfVictimsConfirmed
Indicates the confirmed count of victims associated with an event, incident, or situation.
-
C.
numberOfVictimsClaimed
Indicates the reported count of victims associated with a particular event, incident, or action.
-
D.
numberOfVictimsInSameEvent
Indicates the count of distinct victims involved in the same specific event or incident.
-
E.
casualtiesAssociatedWithEvent
Indicates that certain casualties (deaths or injuries) are linked to, or resulted from, a specific event.
- F. None of above.
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_69f76df54bac8190bd0d3b0eb35cda5f |
completed | May 3, 2026, 3:47 p.m. |
Created at: May 3, 2026, 4:03 p.m.