Triple
T10438805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KBOS runway system |
E246112
|
entity |
| Predicate | supportsTrafficLevel |
P26781
|
FINISHED |
| Object | high-volume operations |
—
|
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: high-volume operations | Statement: [KBOS runway system, supportsTrafficLevel, high-volume operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsTrafficLevel Context triple: [KBOS runway system, supportsTrafficLevel, high-volume operations]
-
A.
supportsTraffic
chosen
Indicates that one entity is capable of handling, carrying, or accommodating the flow or volume of traffic associated with another entity.
-
B.
hasTrafficFeature
Indicates that an entity possesses or is associated with a specific traffic-related characteristic, element, or infrastructure feature.
-
C.
hasCargoTrafficLevel
Indicates the intensity or volume of cargo-related traffic associated with an entity, such as a route, location, or transport facility.
-
D.
hasTrafficManagement
Indicates that an entity implements, uses, or is associated with systems or measures for controlling and optimizing traffic flow.
-
E.
relativeTrafficLevel
Indicates the comparative intensity or volume of traffic between two or more locations, routes, or time periods.
- 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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe083cd881909d2d8ad75d1d94cb |
completed | April 7, 2026, 12:52 p.m. |
| PD | Predicate disambiguation | batch_69d4fb73a5e48190a8df4775bc5da80f |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:14 p.m.