Triple
T10428404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nes (Akershus) |
E245844
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Årnes |
E446461
|
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: Årnes | Statement: [Nes (Akershus), hasSettlement, Årnes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Årnes Context triple: [Nes (Akershus), hasSettlement, Årnes]
-
A.
Årnes
chosen
Årnes is a small Norwegian town situated along the Glomma River, known as a local administrative and commercial center in Nes municipality in Viken county.
-
B.
Ørskog
Ørskog is a village and former municipality in western Norway, located in the county of Møre og Romsdal.
-
C.
Klemetsrud
Klemetsrud is a residential area and neighborhood in the Søndre Nordstrand borough of Oslo, Norway.
-
D.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
E.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
- 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_69d4ea4a7dcc81909a830e08656a1c0c |
completed | April 7, 2026, 11:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87ea554888190bf2ef31e33c0ff14 |
completed | April 10, 2026, 4:37 a.m. |
Created at: April 6, 2026, 12:13 p.m.