Triple
T21129351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ängelholm–Helsingborg Airport |
E520642
|
entity |
| Predicate | hasFlightFrequencyType |
P18239
|
FINISHED |
| Object | scheduled flights |
—
|
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: scheduled flights | Statement: [Ängelholm–Helsingborg Airport, hasFlightFrequencyType, scheduled flights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFlightFrequencyType Context triple: [Ängelholm–Helsingborg Airport, hasFlightFrequencyType, scheduled flights]
-
A.
oftenTravelsWith
Indicates that one entity frequently accompanies another entity when traveling or moving between places.
-
B.
hasTypeOfFlights
chosen
Indicates that an entity offers, includes, or is associated with specific categories or kinds of flights.
-
C.
hasScheduledFlights
Indicates that there are one or more flights planned and set to occur between the related entities according to a schedule.
-
D.
hasLongHaulFlights
Indicates that an entity (such as an airline, route, or airport) operates or is associated with long-distance flights typically covering intercontinental or extended-duration journeys.
-
E.
quantityFlown
Indicates the amount or volume that has been transported by flying from one place to another.
- 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_69e0b50b53048190ae34e8abbe3c5ada |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7223b4c4c8190b9fffa610588651e |
completed | April 21, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69e5f5ed6c8c8190b31092a5d4c3de5d |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 2:56 p.m.