Triple
T10288591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RJOY |
E241300
|
entity |
| Predicate | associatedWithRunwayOrientation |
P6272
|
FINISHED |
| Object | Yao Airport runways |
—
|
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: Yao Airport runways | Statement: [RJOY, associatedWithRunwayOrientation, Yao Airport runways]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithRunwayOrientation Context triple: [RJOY, associatedWithRunwayOrientation, Yao Airport runways]
-
A.
hasRunwayOrientation
chosen
Indicates that a runway is aligned or oriented in a specific directional heading.
-
B.
hasOppositeRunway
Indicates that one runway is paired with another runway that has the opposite or reciprocal orientation or designation.
-
C.
isRunwayOf
Indicates that a physical runway is a component or facility belonging to, used by, or officially associated with a particular airport or airfield.
-
D.
isIntersectingRunwayWith
Indicates that one runway crosses or overlaps with another runway at some point along their lengths.
-
E.
hasRunwayDesignationSide
Indicates that a runway designation is associated with a specific side or direction of the runway (e.g., left, right, or center).
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f117708190928f92ae2611d724 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:41 a.m.