Triple
T13768655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tjeldsund |
E330816
|
entity |
| Predicate | hasIsland |
P970
|
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: [Tjeldsund, hasIsland, Tjeldøya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tjeldøya Context triple: [Tjeldsund, hasIsland, 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.
Austvågøya island
Austvågøya island is a large, mountainous island in Norway’s Lofoten archipelago, known for its dramatic coastal scenery, fishing villages, and popular outdoor tourism.
-
E.
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.
- 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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0233ecc48190b934f085d2501eb1 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00cfb725d48190bdca0a85ca7f440c |
completed | May 10, 2026, 6:34 p.m. |
Created at: April 9, 2026, 10:10 p.m.