Triple
T1310608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orlando International Airport |
E27980
|
entity |
| Predicate | hasRunway |
P105
|
FINISHED |
| Object | Runway 18R/36L |
E156562
|
NE 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 18R/36L | Statement: [Orlando International Airport, hasRunway, Runway 18R/36L]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Runway 18R/36L Context triple: [Orlando International Airport, hasRunway, Runway 18R/36L]
-
A.
Runway 18L/36R
chosen
Runway 18L/36R is a primary north–south runway used for commercial air traffic at Orlando International Airport in Orlando, Florida.
-
B.
Runway 16R/34L
Runway 16R/34L is a primary paved runway used for commercial and general aviation operations at Sacramento International Airport in California.
-
C.
Runway 16L/34R
Runway 16L/34R is a primary paved runway at Sacramento International Airport used for commercial and general aviation takeoffs and landings.
-
D.
Runway 14L/32R
Runway 14L/32R is one of the primary paved runways at Moffett Field in California, used for military, research, and general aviation operations.
-
E.
Runway 14R/32L
Runway 14R/32L is a primary paved runway at Moscow’s Domodedovo International Airport used for handling commercial air traffic.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a496d7d83481908f83085854e51328 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c15490a88190872c3d2698a8f9c9 |
completed | March 1, 2026, 10:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acd47471108190b01121b384d871aa |
completed | March 8, 2026, 1:44 a.m. |
Created at: March 1, 2026, 7:51 p.m.