Triple
T3648616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karmøy |
E77362
|
entity |
| Predicate | hasPart |
P35
|
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: [Karmøy, hasPart, Avaldsnes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avaldsnes Context triple: [Karmøy, hasPart, 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.
Mortensrud
Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
-
C.
Fløya
Fløya is a Norwegian women's football club based in Tromsø that competes in the country's league system.
-
D.
Bremsnes
Bremsnes is a village on the island of Averøya in Møre og Romsdal county, Norway, known for its coastal setting and local church.
-
E.
Leirvik
Leirvik is the main town on the island of Stord in western Norway, serving as an important local commercial and administrative center.
- 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_69ad85de1b988190a45f8dbfebc806fc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc38c22548190a271a69fb832a5a8 |
completed | March 8, 2026, 6:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b48836f5d08190bbf0b6410ed6f766 |
completed | March 13, 2026, 9:57 p.m. |
Created at: March 8, 2026, 3:24 p.m.