Triple
T13714553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Fe Regional Airport |
E328859
|
entity |
| Predicate | hasSecondaryService |
P78228
|
FINISHED |
| Object | general aviation |
—
|
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: general aviation | Statement: [Santa Fe Regional Airport, hasSecondaryService, general aviation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecondaryService Context triple: [Santa Fe Regional Airport, hasSecondaryService, general aviation]
-
A.
hasSecondary
Indicates that an entity is associated with an additional or subordinate counterpart beyond its primary one.
-
B.
hasSecondaryUsage
chosen
Indicates that an entity is associated with an additional, non-primary function or purpose beyond its main intended use.
-
C.
hasSecondaryUser
Indicates that an entity is associated with an additional, non-primary user who also has access to or control over it.
-
D.
hasSecondaryCore
Indicates that an entity possesses an additional, subordinate core component alongside its primary core.
-
E.
hasSecondaryBase
Indicates that an entity possesses or is associated with a secondary or additional base, distinct from its primary base.
- 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_69d80770b9bc81909f70c8c317d53cff |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dd43973cf08190a417d0cca9dd314a |
completed | April 13, 2026, 7:27 p.m. |
| PD | Predicate disambiguation | batch_69dbbe92d77c81908e0244cffb7f78c5 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:54 p.m.