Triple
T12079355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morristown Municipal Airport |
E287636
|
entity |
| Predicate | hasBusinessAviationFocus |
P71775
|
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: [Morristown Municipal Airport, hasBusinessAviationFocus, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBusinessAviationFocus Context triple: [Morristown Municipal Airport, hasBusinessAviationFocus, yes]
-
A.
hasGeneralAviationActivity
Indicates that an entity is involved in or supports non-commercial, private, or recreational aviation operations.
-
B.
servesAviationType
chosen
Indicates that one entity provides services or functions specifically for a particular type or category of aviation.
-
C.
belongsToAviationMarket
Indicates that something is part of, or associated with, the aviation industry market segment.
-
D.
hasAviationTheme
Indicates that something is characterized by or designed around elements related to aviation, such as aircraft, flying, or air travel.
-
E.
hasGeneralAviationFacilities
Indicates that a location or airport provides facilities and services specifically for general aviation operations.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bf4f508190842927e7e0642235 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:48 p.m.