Triple
T10429019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lunner |
E245859
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Oslo region |
E229565
|
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: Oslo region | Statement: [Lunner, locatedNear, Oslo region]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oslo region Context triple: [Lunner, locatedNear, Oslo region]
-
A.
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.
-
B.
Drammensregionen
Drammensregionen is a metropolitan area in southeastern Norway centered around the city of Drammen and its surrounding municipalities.
-
C.
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.
-
D.
Gjøvik Region
Gjøvik Region is a regional area in Innlandet county, Norway, centered around the town of Gjøvik and its surrounding municipalities.
-
E.
Lillehammer region
The Lillehammer region is an area in southeastern Norway known for its winter sports facilities, scenic landscapes, and role as host of the 1994 Winter Olympics.
- 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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea4b4b5881908ae23f8efeea482b |
completed | April 7, 2026, 11:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d90d92510481909135a75b2f582795 |
completed | April 10, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:13 p.m.