Triple
T35430423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clermont County Airport |
E1024040
|
entity |
| Predicate | categoryInUSNAS |
P20157
|
FINISHED |
| Object | general aviation facility |
—
|
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 facility | Statement: [Clermont County Airport, categoryInUSNAS, general aviation facility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: categoryInUSNAS Context triple: [Clermont County Airport, categoryInUSNAS, general aviation facility]
-
A.
classificationByUS
chosen
Indicates a relationship where an entity is assigned a category, status, or type according to a classification system defined or used by the United States.
-
B.
canonicalCategory
Indicates that an entity is assigned to its primary or standard category within a classification system.
-
C.
unitCategory
Indicates the classification or type of unit that an entity belongs to within a defined system or context.
-
D.
categoryDefinedIn
Indicates that a category is formally specified or established within a particular source, context, or definitional framework.
-
E.
categoryAbove
Indicates that one category is positioned higher than another in a hierarchy, ranking, or ordered structure.
- 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_69f76df743c48190aecb6dd79efb0d95 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79ec355048190af30123ceb6efa2b |
completed | May 3, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69f79e4bdbcc8190be7a0d2cf8a77b64 |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:03 p.m.