Triple
T15751183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salten |
E381847
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Fauske |
E381845
|
NE 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: Fauske | Statement: [Salten, contains, Fauske]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fauske Context triple: [Salten, contains, Fauske]
-
A.
Fauske
chosen
Fauske is a small Norwegian town and municipality known for its marble quarries and location in the inland part of Nordland county.
-
B.
Claflin
Claflin is an English surname most notably associated with actor Sam Claflin, known for roles in films such as "The Hunger Games" series and "Me Before You."
-
C.
Fred Meyer
Fred Meyer is a regional American hypermarket chain offering groceries, clothing, home goods, and more under one roof, primarily in the Pacific Northwest.
-
D.
Bartell Drugs
Bartell Drugs is a long-standing regional pharmacy and drugstore chain based in the Seattle area, known for providing prescriptions, health products, and everyday retail goods.
-
E.
Belk
Belk is a major American department store chain primarily located in the Southeastern United States, offering a wide range of apparel, home goods, and beauty products.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e05030e31081908c307a8dc7067db4 |
completed | April 16, 2026, 2:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff876d48588190afec7722cca25633 |
completed | May 9, 2026, 7:13 p.m. |
Created at: April 10, 2026, 4:47 a.m.