Triple
T33237186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 05R/23L |
E850858
|
entity |
| Predicate | runwaySide1 |
P53415
|
FINISHED |
| Object | R |
—
|
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: R | Statement: [Runway 05R/23L, runwaySide1, R]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runwaySide1 Context triple: [Runway 05R/23L, runwaySide1, R]
-
A.
hasRunwaySide
chosen
Indicates that a runway is located on or associated with a particular side or boundary of another feature (such as an airport or airfield area).
-
B.
runway
Indicates a relationship where a runway serves as the takeoff and landing surface used by aircraft at an airport or airfield.
-
C.
runwayAdjacentTo
Indicates that a runway is directly next to or alongside another feature or area, with no significant separation between them.
-
D.
runwaySurface
Indicates the type or condition of the surface material that a runway is made of or covered with.
-
E.
runwayUsedAs
Indicates that a particular runway is being utilized for a specific purpose, role, or operational function.
- 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_69f349613f988190a1eb75467d167122 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7688dd3d08190ad13d0e780570a1c |
completed | May 3, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69f767fcf2f881908bacc7bfc38e68a5 |
completed | May 3, 2026, 3:21 p.m. |
Created at: May 1, 2026, 1:31 a.m.