Triple
T26351808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuusamo Airport |
E662919
|
entity |
| Predicate | focusSeason |
P857
|
FINISHED |
| Object | winter tourism season |
—
|
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: winter tourism season | Statement: [Kuusamo Airport, focusSeason, winter tourism season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusSeason Context triple: [Kuusamo Airport, focusSeason, winter tourism season]
-
A.
dstSeason
Indicates the specific season during which daylight saving time (DST) is in effect for a given context or location.
-
B.
sportSeasonOf
Indicates that one entity is a sports season that belongs to, or is part of, the overall history or schedule of the specified sport.
-
C.
marksSeasonOf
Indicates that one event, date, or phenomenon defines the beginning, end, or occurrence of a particular season.
-
D.
popularSeason
chosen
Indicates that a particular season is widely liked, favored, or frequently chosen by many people.
-
E.
affectedSeason
Indicates that one entity has an influence on, or causes a change in, a particular season.
- 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_69ee8130fc44819094e5ab1da201cd7b |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f68805b4848190b75da14996d52a38 |
completed | May 2, 2026, 11:25 p.m. |
| PD | Predicate disambiguation | batch_69f68609c0b08190a8e1238a4d97c270 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 26, 2026, 10:45 p.m.