Triple
T5805089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oulu |
E128725
|
entity |
| Predicate | airportRankInFinland |
P19832
|
FINISHED |
| Object | one of the busiest airports |
—
|
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: one of the busiest airports | Statement: [Oulu, airportRankInFinland, one of the busiest airports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportRankInFinland Context triple: [Oulu, airportRankInFinland, one of the busiest airports]
-
A.
airportRank
chosen
Indicates the relative position or level assigned to an airport within a ranking or ordered list.
-
B.
distanceToLappeenranta_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Lappeenranta.
-
C.
portRank
Indicates the relative importance or hierarchical ranking assigned to a port within a given system or context.
-
D.
areaRank
Indicates the relative ordering or position of an entity based on the size of its area compared to others.
-
E.
populationShareInFinland
Indicates the proportion of a given population or group relative to the total population within Finland.
- 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_69c00846a0d881909e46841f8e156b64 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b1461a48190be2042dd3823d02e |
completed | March 22, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69c021d477008190946113f9859eeb90 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:52 p.m.