Triple
T17928792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 35 |
E448269
|
entity |
| Predicate | isRunwayEndOf |
P8863
|
FINISHED |
| Object | airport runway |
—
|
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: airport runway | Statement: [Runway 35, isRunwayEndOf, airport runway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isRunwayEndOf Context triple: [Runway 35, isRunwayEndOf, airport runway]
-
A.
runwayEnd
chosen
Indicates that one entity represents the end point or terminus of a runway associated with the other entity.
-
B.
isRunwayOf
Indicates that a physical runway is a component or facility belonging to, used by, or officially associated with a particular airport or airfield.
-
C.
runwayEndHeading
Indicates the directional heading or bearing associated with the end of a runway, typically expressed in degrees relative to north.
-
D.
hasRunwayPresence
Indicates that an entity maintains a physical runway or landing strip suitable for aircraft operations.
-
E.
hasRunwayNumber
Indicates that an airport or airfield runway is assigned a specific identifying number.
- 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_69d8b9f79d14819095540856928f0e25 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a5511a408190973cf5fa1f286a26 |
completed | April 19, 2026, 9:50 a.m. |
| PD | Predicate disambiguation | batch_69e3f8e713d481908b4a126258c18b63 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:20 a.m.