Triple
T10909361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SEQM |
E257652
|
entity |
| Predicate | runwayConfiguration |
P15146
|
FINISHED |
| Object | single main 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: single main runway | Statement: [SEQM, runwayConfiguration, single main runway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runwayConfiguration Context triple: [SEQM, runwayConfiguration, single main runway]
-
A.
hasRunwayConfiguration
chosen
Indicates a specific arrangement or setup of runways associated with an airport, airfield, or similar facility.
-
B.
runwayCharacteristic
Indicates a relationship where specific attributes or features are associated with a runway.
-
C.
runway
Indicates a relationship where a runway serves as the takeoff and landing surface used by aircraft at an airport or airfield.
-
D.
hasRunwayConfigurationRole
Indicates that an entity plays a specific functional role within a particular runway configuration.
-
E.
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.
- 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d77068e5488190bbc881ebf51d6b2e |
completed | April 9, 2026, 9:24 a.m. |
| PD | Predicate disambiguation | batch_69d70d3d69e08190bb369e9a7927142c |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:22 p.m.