Triple
T3393810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albany International Airport |
E71479
|
entity |
| Predicate | hasFireRescueServices |
P3910
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Albany International Airport, hasFireRescueServices, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFireRescueServices Context triple: [Albany International Airport, hasFireRescueServices, yes]
-
A.
hasFireStation
Indicates that a location or area contains or is served by a fire station.
-
B.
fireRescue
chosen
Indicates a relationship where one entity performs or is responsible for rescuing people or property from fires or fire-related emergencies involving another entity.
-
C.
hasEmergencyServices
Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
-
D.
hasEmergencyManagementAgency
Indicates that an entity is associated with or served by a specific emergency management agency responsible for planning, coordinating, or responding to emergencies.
-
E.
hasMunicipalService
Indicates that a municipality provides or is responsible for a specific public service to a given area, facility, or population.
- 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_69ad85a9c4a88190a854019341cb3b60 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb853746c8190bfa1447e6ebbefb3 |
completed | March 8, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69adadf705608190975423779430cc58 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:14 p.m.