Triple
T7853779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skedsmo |
E182120
|
entity |
| Predicate | hasMajorSettlement |
P316
|
FINISHED |
| Object | Skedsmokorset |
E182120
|
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: Skedsmokorset | Statement: [Skedsmo, hasMajorSettlement, Skedsmokorset]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Skedsmokorset Context triple: [Skedsmo, hasMajorSettlement, Skedsmokorset]
-
A.
Skedsmo
chosen
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.
-
B.
Storslett
Storslett is a small village and administrative center in Nordreisa Municipality in Troms og Finnmark county in northern Norway.
-
C.
Kongsseteren
Kongsseteren is a historic winter residence and retreat used by the Norwegian royal family near Oslo.
-
D.
Skjåk
Skjåk is a rural municipality in Innlandet county, Norway, known for its mountainous landscapes, national parks, and dry inland climate.
-
E.
Skeid
Skeid is a Norwegian sports club best known for its football team and local rivalry with Lyn in Oslo.
- 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb18ed56d481909266d862e0ae152d |
completed | March 31, 2026, 12:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5b1e9e808190a0eb2dea5288e743 |
completed | March 31, 2026, 5:26 a.m. |
Created at: March 30, 2026, 4:51 p.m.