Triple
T28458466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MMV |
E716782
|
entity |
| Predicate | associatedWithAirportOwnership |
P169557
|
FINISHED |
| Object | public |
—
|
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: public | Statement: [MMV, associatedWithAirportOwnership, public]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithAirportOwnership Context triple: [MMV, associatedWithAirportOwnership, public]
-
A.
associatedWithAirportType
Indicates that an entity has a connection or linkage to a specific category or type of airport.
-
B.
associatedWithAirportName
Indicates a relationship where an entity is linked or connected to a specific airport by its name.
-
C.
associatedWithAirportCode
Indicates that one entity has a relationship or connection to an airport identified by a specific airport code.
-
D.
associatedWithAirportRole
Indicates a relationship where an entity is linked to a specific functional role or responsibility within an airport context.
-
E.
airportOwnershipModel
chosen
Indicates the type or structure of ownership or governance arrangement under which an airport is held or operated.
- 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_69efd6b76f8c8190a7ba908aca280942 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_6a0160834e388190908591b300954d29 |
completed | May 11, 2026, 4:52 a.m. |
| PD | Predicate disambiguation | batch_6a01602a83408190a11d754bdc7da0e9 |
completed | May 11, 2026, 4:50 a.m. |
Created at: April 28, 2026, 1:55 a.m.