Triple
T36460358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cold Bay Airport |
E898271
|
entity |
| Predicate | hasLongRunwayRelativeToRegion |
P199848
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Cold Bay Airport, hasLongRunwayRelativeToRegion, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLongRunwayRelativeToRegion Context triple: [Cold Bay Airport, hasLongRunwayRelativeToRegion, true]
-
A.
hasLongerReachThan
Indicates that one entity can extend, influence, or physically reach farther than another entity.
-
B.
hasLongDistanceConnections
Indicates that an entity maintains connections or relationships that span a large geographic or conceptual distance.
-
C.
hasRegionalCenterNearby
Indicates that a regional center is located in close proximity to the referenced entity.
-
D.
hasBroadRegion
Indicates that an entity is associated with, located in, or applicable to a relatively large or general geographic or conceptual region.
-
E.
hasRelativePositionInCity
Indicates that one entity occupies a specific spatial or positional relationship within the boundaries or layout of a particular city.
- 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_69f76e57f08481908593bd0bc34581c8 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff5b233e9c8190adc06cca0758986b |
completed | May 9, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69ff5a5682108190a006b23c4fcdcc7c |
completed | May 9, 2026, 4:01 p.m. |
| PDg | Predicate description generation | batch_69ff5b224b8c8190bd0955876098ecc8 |
completed | May 9, 2026, 4:04 p.m. |
Created at: May 3, 2026, 4:10 p.m.