Triple
T15014331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Molde Municipality |
E377918
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Eidsvåg |
E524996
|
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: Eidsvåg | Statement: [Molde Municipality, contains, Eidsvåg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eidsvåg Context triple: [Molde Municipality, contains, Eidsvåg]
-
A.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
B.
Vennesla
Vennesla is a municipality in Agder county in southern Norway, known for its industrial heritage and scenic river valley setting.
-
C.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
-
D.
Ørskog
chosen
Ørskog is a village and former municipality in western Norway, located in the county of Møre og Romsdal.
-
E.
Engerdal
Engerdal is a sparsely populated municipality in Innlandet county, Norway, known for its vast forests, lakes, and proximity to the Swedish border.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7623c3c819092ca36b358b01842 |
completed | April 15, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff133571008190b7e7867208095b90 |
completed | May 9, 2026, 10:57 a.m. |
Created at: April 10, 2026, 2:55 a.m.