Triple
T27896059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 17L/35R |
E705494
|
entity |
| Predicate | hasOrientationType |
P12663
|
FINISHED |
| Object | roughly north–south |
—
|
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: roughly north–south | Statement: [Runway 17L/35R, hasOrientationType, roughly north–south]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOrientationType Context triple: [Runway 17L/35R, hasOrientationType, roughly north–south]
-
A.
hasOrientation
chosen
Indicates that one entity is positioned or directed in a specific spatial or conceptual alignment relative to a reference frame or another entity.
-
B.
hasOrientationInUse
Indicates that an entity, when in use or operation, is oriented in a specific direction or spatial alignment.
-
C.
hasOrientationTable
Indicates that an entity is associated with or defined by a specific orientation table that describes its directional or rotational properties.
-
D.
hasAestheticOrientation
Indicates that an entity holds or exhibits a particular aesthetic preference, style, or orientation in relation to another entity or concept.
-
E.
hasRegionalOrientation
Indicates that an entity is oriented toward, focused on, or primarily associated with a specific geographic region.
- 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_69ef96b490ac8190a412d04c5d009f3e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 27, 2026, 6:38 p.m.