Triple
T35820637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 24R at LAX |
E1035488
|
entity |
| Predicate | isParallelRunwayInSystem |
P11810
|
FINISHED |
| Object | LAX north runway complex |
—
|
NE NERFINISHED |
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: LAX north runway complex | Statement: [Runway 24R at LAX, isParallelRunwayInSystem, LAX north runway complex]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isParallelRunwayInSystem Context triple: [Runway 24R at LAX, isParallelRunwayInSystem, LAX north runway complex]
-
A.
hasParallelRunwaySystemRole
Indicates that an entity holds a specific role or function within a parallel runway system.
-
B.
hasParallelRunwayIndicator
Indicates that one runway serves as a parallel counterpart or reference indicator for another runway within an airport or airfield.
-
C.
hasParallelRunway
chosen
Indicates that one runway is parallel in orientation and alignment to another runway.
-
D.
hasOppositeRunway
Indicates that one runway is paired with another runway that has the opposite or reciprocal orientation or designation.
-
E.
isSingleRunwayForAirport
Indicates that a runway is the only (single) runway serving a particular 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_69f76e185ffc8190880b3cdf51decd38 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ffb69812808190a751853b30183e65 |
completed | May 9, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69ffb63bdda88190a9dd8426dc0bad43 |
completed | May 9, 2026, 10:33 p.m. |
Created at: May 3, 2026, 4:06 p.m.