Triple
T13039926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tjeldsundet |
E327164
|
entity |
| Predicate | hasCoastlineOn |
P212
|
FINISHED |
| Object | Tjeldøya |
E195938
|
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: Tjeldøya | Statement: [Tjeldsundet, hasCoastlineOn, Tjeldøya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tjeldøya Context triple: [Tjeldsundet, hasCoastlineOn, Tjeldøya]
-
A.
Tjeldøya
chosen
Tjeldøya is an island in northern Norway known for its rugged coastal landscape and location within the Ofoten region.
-
B.
Storøya
Storøya is an island located in the lake Tyrifjorden in Norway.
-
C.
Kvitøya
Kvitøya is a remote, mostly ice-covered island in the far northeastern part of the Svalbard archipelago in the Arctic Ocean.
-
D.
Tromsøya island
Tromsøya island is a Norwegian island in Troms og Finnmark county that hosts the city center of Tromsø and is known for its Arctic location and vibrant cultural life.
-
E.
Flakstadøya
Flakstadøya is a scenic island in Norway’s Lofoten archipelago, known for its dramatic mountains, fishing villages, and coastal landscapes.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d9804d8e3081909584c93df099859a |
completed | April 10, 2026, 10:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a20a5ec8190bc054b3d7cae003b |
completed | May 3, 2026, 8:41 a.m. |
Created at: April 9, 2026, 8:55 p.m.