Triple
T33696090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MDE |
E863315
|
entity |
| Predicate | associatedAirportPrimaryRunwayLength |
P6291
|
FINISHED |
| Object | approximately 3500 metres |
—
|
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: approximately 3500 metres | Statement: [MDE, associatedAirportPrimaryRunwayLength, approximately 3500 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedAirportPrimaryRunwayLength Context triple: [MDE, associatedAirportPrimaryRunwayLength, approximately 3500 metres]
-
A.
isPrimaryRunwayOf
Indicates that a runway serves as the main or principal runway for a particular airport or airfield.
-
B.
runwayLength
chosen
Indicates the length of a runway associated with an airport or airfield.
-
C.
hasLongestRunwayIn
Indicates that an entity possesses the runway of greatest length within a specified location or region.
-
D.
hasSinglePrimaryRunway
Indicates that an airport or airfield possesses exactly one main runway used as its primary operational runway.
-
E.
hasPrimaryAirportRole
Indicates that an entity holds the main or principal functional role associated with an 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.