Triple
T13219293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | County Road 64 |
E314705
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Averøya |
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: Averøya | Statement: [County Road 64, passesThrough, Averøya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Averøya Context triple: [County Road 64, passesThrough, Averøya]
-
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.
Spjærøy
Spjærøy is one of the main inhabited islands in the Hvaler archipelago in southeastern Norway, known for its coastal scenery and holiday cottages.
-
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.
Andøya
Andøya is a large Norwegian island in Nordland county, known for its dramatic coastal landscapes, space center, and rich bird and whale-watching opportunities.
-
E.
Flekkerøy
Flekkerøy is a populated island and coastal community in southern Norway, known for its maritime heritage and proximity to the city of Kristiansand.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf392e08190949ee4d194566395 |
completed | April 10, 2026, 11:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbac754aec8190a5b975c9965eef61 |
completed | May 6, 2026, 9:02 p.m. |
Created at: April 9, 2026, 9:18 p.m.