Triple
T13328487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lillestrøm region |
E317503
|
entity |
| Predicate | hasPopulationCenter |
P2106
|
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: [Lillestrøm region, hasPopulationCenter, Skedsmokorset]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Skedsmokorset Context triple: [Lillestrøm region, hasPopulationCenter, 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.
Terningmoen
Terningmoen is a Norwegian Army military camp and training area located near Elverum in Innlandet county, Norway.
-
D.
Skjetten
Skjetten is a suburban residential area in Lillestrøm municipality in Viken county, Norway, located northeast of Oslo.
-
E.
Kongsseteren
Kongsseteren is a historic winter residence and retreat used by the Norwegian royal family near 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9992e4f908190a6f172bf910cffb8 |
completed | April 11, 2026, 12:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f329e148190a7741344b27ea663 |
completed | May 3, 2026, 10:10 a.m. |
Created at: April 9, 2026, 9:30 p.m.