Triple
T18078761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Søndre Land |
E432628
|
entity |
| Predicate | hasNeighbour |
P5707
|
FINISHED |
| Object | Nordre Land |
—
|
NE NERFINISHED |
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: Nordre Land | Statement: [Søndre Land, hasNeighbour, Nordre Land]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nordre Land Context triple: [Søndre Land, hasNeighbour, Nordre Land]
-
A.
Nordre Land
chosen
Nordre Land is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and agricultural landscape in the traditional district of Land.
-
B.
Nordlandet
Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
-
C.
Helgeland
Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
-
D.
Nordhordland
Nordhordland is a traditional district in western Norway known for its coastal landscapes, fjords, and proximity to the city of Bergen.
-
E.
Jørpeland
Jørpeland is a town in Rogaland county, Norway, known as a local industrial and service hub and a gateway to the nearby Lysefjord and Preikestolen (Pulpit Rock).
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4d9f6a85481909894c39c8be98d5d |
completed | April 19, 2026, 1:34 p.m. |
Created at: April 10, 2026, 10:27 a.m.