Triple
T27558393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skjetten |
E695705
|
entity |
| Predicate | hasLocalShoppingFacility |
P16039
|
FINISHED |
| Object | Skjetten Senter |
—
|
NE NERFINISHED |
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: Skjetten Senter | Statement: [Skjetten, hasLocalShoppingFacility, Skjetten Senter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalShoppingFacility Context triple: [Skjetten, hasLocalShoppingFacility, Skjetten Senter]
-
A.
hasConvenienceStore
Indicates that one entity possesses, contains, or is associated with a convenience store.
-
B.
hasGroceryStores
Indicates that one entity possesses, contains, or is associated with one or more grocery stores.
-
C.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
D.
hasShoppingMall
chosen
Indicates that one entity possesses, contains, or includes a shopping mall within its area or domain.
-
E.
hasShoppingDistrict
Indicates that a place contains or is associated with a designated area where multiple shops and commercial retail activities are concentrated.
- 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_69ef5387e97c8190a9dab040d21cd048 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f74062b9388190b30546cf700a825c |
completed | May 3, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69f73c802b848190b61a416b7488bd96 |
completed | May 3, 2026, 12:16 p.m. |
Created at: April 27, 2026, 1:38 p.m.