Triple
T36794882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aires Flight 8250 |
E909155
|
entity |
| Predicate | runwayImpact |
P188150
|
FINISHED |
| Object | short of 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: short of runway | Statement: [Aires Flight 8250, runwayImpact, short of runway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runwayImpact Context triple: [Aires Flight 8250, runwayImpact, short of runway]
-
A.
runwayPerformance
Indicates the performance characteristics or behavior of an entity (such as an aircraft or vehicle) when operating on a runway, including factors like acceleration, deceleration, and required distances.
-
B.
runway
Indicates a relationship where a runway serves as the takeoff and landing surface used by aircraft at an airport or airfield.
-
C.
runwayLanding
Indicates that an aircraft performs a landing operation on a specific runway.
-
D.
runwayCrosses
Indicates that one runway intersects or passes across another runway or designated path.
-
E.
runwayUsage
Indicates that a particular runway is being used or assigned for aircraft operations such as takeoffs or landings.
- F. None of above. chosen
Provenance (4 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_69f76e7b98888190899b6478a82ad6ae |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fba2877b248190a974eb092243c0c4 |
completed | May 6, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69fb8d06a1b48190a937aa410d159dfa |
completed | May 6, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69fba28684208190921694f23e350c3b |
completed | May 6, 2026, 8:20 p.m. |
Created at: May 3, 2026, 4:12 p.m.