Triple
T13808563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kristians amt |
E331820
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Skjåk |
E433532
|
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: Skjåk | Statement: [Kristians amt, contains, Skjåk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Skjåk Context triple: [Kristians amt, contains, Skjåk]
-
A.
Skjåk
chosen
Skjåk is a rural municipality in Innlandet county, Norway, known for its mountainous landscapes, national parks, and dry inland climate.
-
B.
Evenskjer
Evenskjer is a small village in Northern Norway that serves as an administrative and service center in the Troms region.
-
C.
Gjerdrum
Gjerdrum is a small rural municipality in Viken county, Norway, known for its agricultural landscape and proximity to the Oslo metropolitan area.
-
D.
Skedsmo
Skedsmo is a former municipality in Viken county, Norway, located northeast of Oslo and known for its suburban communities and historical ties to the Oslo region.
-
E.
Skøyen
Skøyen is a neighborhood in western Oslo, Norway, known as a busy residential and commercial hub with strong public transport connections.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de026eae8481908b8880635e6a9152 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7d20f548190a9f48e8c613abed4 |
completed | May 7, 2026, 8:36 p.m. |
Created at: April 9, 2026, 10:12 p.m.