Triple
T786513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Norway |
E16813
|
entity |
| Predicate | hasPopularWinterSports |
P19624
|
FINISHED |
| Object | skiing |
—
|
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: skiing | Statement: [Eastern Norway, hasPopularWinterSports, skiing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPopularWinterSports Context triple: [Eastern Norway, hasPopularWinterSports, skiing]
-
A.
hasSkiResortNearby
Indicates that one location is situated close enough to another location that it can be considered to have a ski resort in its vicinity.
-
B.
hasSkiLifts
Indicates that one location or facility is equipped with ski lifts that provide transportation for skiers or visitors.
-
C.
alpineSkiingVenue
Indicates that one entity serves as a venue or location where alpine skiing activities or events take place in relation to another entity.
-
D.
hasPopularResort
Indicates that a location or area contains or is associated with a resort that is widely visited or well-liked.
-
E.
hasSkiableArea
Indicates that an entity possesses an area of terrain that can be used for skiing.
- F. None of above. chosen
Provenance (4 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a77fcc6881908a025bb21e44ad56 |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a50db97c8190a1c55673f4a357b4 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a67e69288190b3dc278c5bd94155 |
completed | March 1, 2026, 8:50 p.m. |
Created at: March 1, 2026, 7:38 p.m.