Triple
T4265596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Civil Reserve Air Fleet |
E96816
|
entity |
| Predicate | benefitToAirlines |
P487
|
FINISHED |
| Object | access to peacetime Department of Defense airlift business |
—
|
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: access to peacetime Department of Defense airlift business | Statement: [Civil Reserve Air Fleet, benefitToAirlines, access to peacetime Department of Defense airlift business]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitToAirlines Context triple: [Civil Reserve Air Fleet, benefitToAirlines, access to peacetime Department of Defense airlift business]
-
A.
airlinesUse
Indicates that certain airlines operate, employ, or make use of a specified resource, service, or system.
-
B.
benefits
chosen
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
-
C.
revenueImportanceForAirlines
Indicates how important a given source, activity, or factor is in generating revenue for airlines.
-
D.
mainAirlineFocus
Indicates that an airline is the primary or central focus of attention, operations, or analysis in a given context.
-
E.
associatedWithFrequentFlyerProgram
Indicates that an entity has a connection or involvement with a frequent flyer program, such as membership, participation, or affiliation.
- 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_69b34543f06c8190915ebb1a4574ffa9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34fcad0a881908e1cac0a6da5a321 |
completed | March 12, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_69b347f8dcb08190a725c1f7fb5a7466 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:07 p.m.