Triple
T29393787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NWI |
E745439
|
entity |
| Predicate | hasRunwayAtAirport |
P126744
|
FINISHED |
| Object | Runway 09/27 |
—
|
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: Runway 09/27 | Statement: [NWI, hasRunwayAtAirport, Runway 09/27]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRunwayAtAirport Context triple: [NWI, hasRunwayAtAirport, Runway 09/27]
-
A.
hasRunwayPresence
Indicates that an entity maintains a physical runway or landing strip suitable for aircraft operations.
-
B.
hasRunwaysAt
chosen
Indicates that a location or facility possesses one or more runways situated at that place.
-
C.
hasRunwayAccessTo
Indicates that one location or facility is directly connected to another via a usable runway, allowing aircraft to move between them without leaving runway infrastructure.
-
D.
hasRunwayCount
Indicates the number of runways that a given entity (such as an airport) possesses.
-
E.
hasRunwayType
Indicates that an airport or airfield has a runway of a specified type or surface classification.
- 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_69f0a79dfabc81908755382ee47791e2 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ed5d008190831cf8e44cce28af |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 28, 2026, 2:44 p.m.