Triple
T2912324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Froland |
E63709
|
entity |
| Predicate | neighbouringMunicipality |
P33892
|
FINISHED |
| Object | Åmli |
E150931
|
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: Åmli | Statement: [Froland, neighbouringMunicipality, Åmli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Åmli Context triple: [Froland, neighbouringMunicipality, Åmli]
-
A.
Åmli
chosen
Åmli is a rural municipality in Agder county in southern Norway, known for its forested landscapes, rivers, and outdoor recreation opportunities.
-
B.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
-
C.
Solbo
Solbo is a locality within Botkyrka Municipality in Stockholm County, Sweden.
-
D.
Hafslund
Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
-
E.
Bjug Harstad
Bjug Harstad was a Norwegian-American Lutheran minister and educator best known for establishing Pacific Lutheran University in Washington State.
- 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_69ab4c44ab448190b9411324e8a1fc1d |
completed | March 6, 2026, 9:51 p.m. |
| NER | Named-entity recognition | batch_69abe0eb77708190b745b887f3b9a618 |
completed | March 7, 2026, 8:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0562014fc8190b7b702fa40682382 |
completed | March 10, 2026, 5:34 p.m. |
Created at: March 6, 2026, 10:11 p.m.