Triple
T545655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RNAS Yeovilton |
E12726
|
entity |
| Predicate | hasRunwayType |
P15527
|
FINISHED |
| Object | paved 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: paved runway | Statement: [RNAS Yeovilton, hasRunwayType, paved runway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRunwayType Context triple: [RNAS Yeovilton, hasRunwayType, paved runway]
-
A.
hasRunwayNumber
Indicates that an airport or airfield runway is assigned a specific identifying number.
-
B.
hasRunwayOrientation
Indicates that a runway is aligned or oriented in a specific directional heading.
-
C.
hasRunwayConfiguration
Indicates a specific arrangement or setup of runways associated with an airport, airfield, or similar facility.
-
D.
runway
Indicates a relationship where a runway serves as the takeoff and landing surface used by aircraft at an airport or airfield.
-
E.
hasRunwayLighting
Indicates that a runway is equipped with lighting systems to aid visibility and operations, typically during low-light or night conditions.
- 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_69a49334226c81908b0ea1689ef6aa3f |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a498dfec5c81908b76d723b30dc2f0 |
completed | March 1, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69a494b8098481908097228db8ad0262 |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a49858abd48190bd4b002a93e4a908 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:32 p.m.