Triple
T28791919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vaasa Airport |
E726976
|
entity |
| Predicate | trafficScope |
P165590
|
FINISHED |
| Object | regional |
—
|
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: regional | Statement: [Vaasa Airport, trafficScope, regional]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trafficScope Context triple: [Vaasa Airport, trafficScope, regional]
-
A.
trafficFocus
Indicates a focus of attention or priority given to a particular traffic element, flow, or direction within a transportation or network context.
-
B.
trafficType
Indicates the category or nature of traffic involved in a given interaction, flow, or connection (e.g., type of network, data, or transport traffic).
-
C.
traffics
Indicates engaging in the buying, selling, or illicit trading of someone or something, typically as part of an ongoing commercial or criminal operation.
-
D.
trafficShare
Indicates the proportion of total traffic or visits that one entity receives relative to others within a defined context or time period.
-
E.
trafficLevel
Indicates the degree of congestion or flow intensity present in a transportation network or route at a given time.
- 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_69f0319aabec81908368720196f69a35 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f6596b210481908af6cd555748f75b |
completed | May 2, 2026, 8:07 p.m. |
| PD | Predicate disambiguation | batch_69f65760fd3081908ffe014a5e2bf069 |
completed | May 2, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f658ebeca4819096beb3f98f73fe31 |
completed | May 2, 2026, 8:05 p.m. |
Created at: April 28, 2026, 6:23 a.m.