Triple
T32003635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FDNY Ladder Company 86 |
E817199
|
entity |
| Predicate | primaryApparatusType |
—
|
GENERATED |
| Object | aerial ladder truck |
—
|
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: primaryApparatusType Context triple: [FDNY Ladder Company 86, primaryApparatusType, aerial ladder truck]
-
A.
hasTypeOfApparatus
chosen
Indicates that one entity is associated with, or utilizes, a specific kind or category of apparatus.
-
B.
describesApparatus
Indicates that one entity provides a description or specification of an apparatus used by another entity or within a particular context.
-
C.
hasCriticalApparatus
Indicates that a text or document is accompanied by a critical apparatus, i.e., scholarly notes, variant readings, and editorial commentary that analyze and support the main content.
-
D.
vehicleType
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
-
E.
mainVehicle
Indicates that one vehicle is the primary or most important vehicle associated with a given entity or context.
- 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_69f348f8ce388190ae84376b1f348f12 |
completed | April 30, 2026, 12:20 p.m. |
Created at: May 1, 2026, 12:14 a.m.