Triple
T15031509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henderson–Oxford Airport |
E378360
|
entity |
| Predicate | has runway orientation |
P6272
|
FINISHED |
| Object | 09/27 |
—
|
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: 09/27 | Statement: [Henderson–Oxford Airport, has runway orientation, 09/27]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: has runway orientation Context triple: [Henderson–Oxford Airport, has runway orientation, 09/27]
-
A.
hasRunwayOrientation
chosen
Indicates that a runway is aligned or oriented in a specific directional heading.
-
B.
runwayCharacteristic
Indicates a relationship where specific attributes or features are associated with a runway.
-
C.
isPrimaryRunwayOf
Indicates that a runway serves as the main or principal runway for a particular airport or airfield.
-
D.
runway
Indicates a relationship where a runway serves as the takeoff and landing surface used by aircraft at an airport or airfield.
-
E.
numberOfRunways
Indicates the quantity of runways associated with a given entity, such as an airport or airfield.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7e2416081908dfba48d7f7b4a84 |
completed | April 15, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69de9a67cbc481909c19c2de57de4eb7 |
completed | April 14, 2026, 7:50 p.m. |
Created at: April 10, 2026, 2:59 a.m.