Triple
T4535069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hallingdal |
E107387
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Nesbyen |
E440168
|
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: Nesbyen | Statement: [Hallingdal, contains, Nesbyen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nesbyen Context triple: [Hallingdal, contains, Nesbyen]
-
A.
Nesbyen
chosen
Nesbyen is a small town and municipality in southeastern Norway known for its inland valley setting, historic wooden buildings, and notably warm summer temperatures.
-
B.
Bremsnes
Bremsnes is a village on the island of Averøya in Møre og Romsdal county, Norway, known for its coastal setting and local church.
-
C.
Fosnes
Fosnes was a former rural municipality in Trøndelag county, Norway, known for its coastal landscape and small, dispersed population.
-
D.
Trondenes
Trondenes is a historic former municipality and parish in northern Norway, known for its medieval stone church and role as an administrative center in the Harstad region.
-
E.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of 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_69bd43f922788190b7edfa294e39b178 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57a2301c8190aa59280a16750156 |
completed | March 20, 2026, 2:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdb9193e2481908901b9b4eb307da8 |
completed | March 20, 2026, 9:16 p.m. |
Created at: March 20, 2026, 1:04 p.m.