Triple
T13042939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lee's Summit Fire Department |
E327241
|
entity |
| Predicate | usesApparatus |
P2728
|
FINISHED |
| Object | fire engines |
—
|
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: fire engines | Statement: [Lee's Summit Fire Department, usesApparatus, fire engines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesApparatus Context triple: [Lee's Summit Fire Department, usesApparatus, fire engines]
-
A.
describesApparatus
Indicates that one entity provides a description or specification of an apparatus used by another entity or within a particular context.
-
B.
usesRollingStock
Indicates that one entity employs or operates specific rolling stock (such as rail vehicles) in its activities or services.
-
C.
usesEquipment
chosen
Indicates that an entity employs or operates a particular piece of equipment to perform an action or fulfill a function.
-
D.
usesArmoredVehicle
Indicates that an entity employs or operates an armored vehicle in performing an action or fulfilling a role.
-
E.
hasArrestingGear
Indicates that an entity is equipped with a system or mechanism used to rapidly decelerate and stop another entity, typically during landing or capture.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d98a9829b48190b23624b6b3df4600 |
completed | April 10, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69d9803aca4c8190b1015cd159cc47a9 |
completed | April 10, 2026, 10:56 p.m. |
Created at: April 9, 2026, 8:56 p.m.