Triple
T5426482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2011 Norway attacks |
E121375
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Utøya |
E489962
|
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: Utøya | Statement: [2011 Norway attacks, location, Utøya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Utøya Context triple: [2011 Norway attacks, location, Utøya]
-
A.
Utøya
chosen
Utøya is a small island in Norway best known as the site of the 2011 mass shooting during a youth camp organized by the Labour Party.
-
B.
Borkenes
Borkenes is a small coastal village in northern Norway known for its scenic surroundings and traditional fishing and farming activities.
-
C.
Øye
Øye is a small Norwegian village in the Sunnmøre region, known for its dramatic fjord landscape and the historic Hotel Union Øye.
-
D.
Rennesøy
Rennesøy is an island and former municipality in Rogaland county, southwestern Norway, known for its coastal landscape and proximity to the city of Stavanger.
-
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_69bd463b58d88190b258261573de9e91 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8817a2048190a76805da03cfa09b |
completed | March 20, 2026, 5:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf3abfc7e88190b8f0a31b61c33973 |
completed | March 22, 2026, 12:41 a.m. |
Created at: March 20, 2026, 2:06 p.m.