Triple
T5098092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Møre og Romsdal |
E114915
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Averøy |
E79229
|
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: Averøy | Statement: [Møre og Romsdal, containsSettlement, Averøy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Averøy Context triple: [Møre og Romsdal, containsSettlement, Averøy]
-
A.
Averøya
chosen
Averøya is a scenic Norwegian island known for its coastal landscapes and its location along the famous Atlantic Ocean Road in Western Norway.
-
B.
Storøya
Storøya is an island located in the lake Tyrifjorden in Norway.
-
C.
Værøy
Værøy is a small, scenic island and fishing community in northern Norway, known for its dramatic coastal landscapes and part of the Lofoten archipelago.
-
D.
Rolløya
Rolløya is an island located in Troms county in northern Norway, known for its rugged coastal landscape and Arctic climate.
-
E.
Vannøya
Vannøya is a large island in northern Norway known for its rugged coastal landscape, fishing communities, and Arctic climate.
- 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_69bd443fc49c819089629c00e311310c |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7567d21081909227ed8f08b74c71 |
completed | March 20, 2026, 4:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69becfc467008190ae704139f21edae2 |
completed | March 21, 2026, 5:05 p.m. |
Created at: March 20, 2026, 1:40 p.m.