Triple
T21953863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asker Station |
E542132
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Oslo region |
—
|
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: Oslo region | Statement: [Asker Station, serves, Oslo region]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oslo region Context triple: [Asker Station, serves, Oslo region]
-
A.
Oslo Marka region
The Oslo Marka region is a vast forested recreational area surrounding Oslo, Norway, known for its extensive hiking, skiing, and outdoor activity opportunities.
-
B.
Bergen region
The Bergen region is a coastal metropolitan area in western Norway centered on the city of Bergen and its surrounding islands and municipalities.
-
C.
Greater Oslo Region
chosen
The Greater Oslo Region is the metropolitan area surrounding Norway’s capital, encompassing Oslo and its neighboring municipalities as a unified economic and commuter region.
-
D.
Drammensregionen
Drammensregionen is a metropolitan area in southeastern Norway centered around the city of Drammen and its surrounding municipalities.
-
E.
Oslo county
Oslo county is Norway’s capital county, encompassing the city of Oslo and serving as the country’s political, economic, and cultural center.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1243dfb4081909bc7a722843ffea7 |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:59 p.m.