Triple
T15763961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haugalandet |
E382170
|
entity |
| Predicate | hasCulturalSite |
P1098
|
FINISHED |
| Object | Avaldsnes |
E376431
|
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: Avaldsnes | Statement: [Haugalandet, hasCulturalSite, Avaldsnes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avaldsnes Context triple: [Haugalandet, hasCulturalSite, Avaldsnes]
-
A.
Avaldsnes
chosen
Avaldsnes is a historic village in Rogaland county, Norway, known as one of the country’s oldest royal seats and a key center in Viking-era history.
-
B.
Alstahaug
Alstahaug is a coastal municipality in northern Norway known for its historic church, island landscapes, and maritime heritage.
-
C.
Jostedøla
Jostedøla is a river in Vestland county, Norway, originating from the Jostedalsbreen glacier and flowing through the Jostedalen valley before emptying into the Sognefjord.
-
D.
Orkanger
Orkanger is a town in Trøndelag county, Norway, known as a regional commercial and service hub by the Orkdalsfjorden.
-
E.
Åndalsnes
Åndalsnes is a small Norwegian town known as a gateway to dramatic fjord and mountain landscapes, including popular hiking and climbing areas like Romsdalseggen and Trollveggen.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b6c9fc8190a1bcf763c4b04b12 |
completed | April 16, 2026, 3 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe66d78c81908308fc16c8d4e19c |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 4:47 a.m.