Triple
T33696106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MDE |
E863315
|
entity |
| Predicate | associatedAirportServesPassengerTrafficType |
P58803
|
FINISHED |
| Object | domestic |
—
|
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: domestic | Statement: [MDE, associatedAirportServesPassengerTrafficType, domestic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedAirportServesPassengerTrafficType Context triple: [MDE, associatedAirportServesPassengerTrafficType, domestic]
-
A.
associatedAirportServes
Indicates that a given airport provides service to, or is used by, the associated entity (such as a city, region, or facility).
-
B.
servedPassengerTraffic
Indicates that an entity has provided transportation services to a certain volume or set of passengers.
-
C.
servesPassengerTrafficTo
Indicates that a transportation facility or service provides regular passenger traffic access or operations to a particular location or area.
-
D.
servesPassengerTrafficType
Indicates that a transportation facility or service accommodates a specified type or category of passenger traffic.
-
E.
associatedAirport
chosen
Indicates a relationship where an entity is linked or connected to a specific airport, typically as its relevant or corresponding airport.
- 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_69f3498723a08190ac034339cc78eade |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:43 a.m.