Triple
T15139683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lelystad Airport |
E361650
|
entity |
| Predicate | plannedTrafficType |
P27465
|
FINISHED |
| Object | holiday traffic |
—
|
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: holiday traffic | Statement: [Lelystad Airport, plannedTrafficType, holiday traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plannedTrafficType Context triple: [Lelystad Airport, plannedTrafficType, holiday traffic]
-
A.
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).
-
B.
originalTrafficType
Indicates the initial category or source classification of traffic before any changes, redirects, or reattributions occur.
-
C.
hasCargoTrafficType
Indicates that an entity is associated with a specific type or category of cargo traffic it handles or supports.
-
D.
servesPassengerTrafficType
Indicates that a transportation facility or service accommodates a specified type or category of passenger traffic.
-
E.
majorTrafficType
chosen
Indicates the primary kind of traffic or flow that predominantly characterizes a given route, segment, or transportation context.
- 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005c46a248190a2364092d40274f3 |
completed | April 15, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69deb9713fe881909dec2fd3f6c84b39 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:07 a.m.