Triple
T7873778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince Rupert Airport |
E182800
|
entity |
| Predicate | offersScheduledFlights |
P19814
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Prince Rupert Airport, offersScheduledFlights, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersScheduledFlights Context triple: [Prince Rupert Airport, offersScheduledFlights, yes]
-
A.
hasScheduledFlights
chosen
Indicates that there are one or more flights planned and set to occur between the related entities according to a schedule.
-
B.
offersSchedule
Indicates that one entity provides or makes available a specific schedule to another entity or for a particular purpose.
-
C.
airlineService
Indicates that an airline operates transportation services (such as flights) between specified locations or for specified routes.
-
D.
hasTypeOfFlights
Indicates that an entity offers, includes, or is associated with specific categories or kinds of flights.
-
E.
numberOfFlights
Indicates the total count of flights associated with a given entity or within a specified 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_69ca828a17248190b46defe758bc5ad3 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39a7f1648190980db4db1a800189 |
completed | March 31, 2026, 3:04 a.m. |
| PD | Predicate disambiguation | batch_69cae928e1b88190b0620f4c4f03bc7d |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:56 p.m.