Triple
T3648617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karmøy |
E77362
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Skudeneshavn |
E414652
|
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: Skudeneshavn | Statement: [Karmøy, hasPart, Skudeneshavn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Skudeneshavn Context triple: [Karmøy, hasPart, Skudeneshavn]
-
A.
Skudeneshavn
chosen
Skudeneshavn is a historic coastal town in southwestern Norway known for its well-preserved wooden architecture and maritime heritage.
-
B.
Bremsnes
Bremsnes is a village on the island of Averøya in Møre og Romsdal county, Norway, known for its coastal setting and local church.
-
C.
Grimstad
Grimstad is a coastal town and municipality in southern Norway known for its maritime heritage, charming wooden houses, and role as a summer tourist destination.
-
D.
Haugesund
Haugesund is a coastal city in southwestern Norway known for its maritime heritage, shipbuilding industry, and annual film and jazz festivals.
-
E.
Norheimsund
Norheimsund is a village in western Norway known as a regional center in the Hardanger region, noted for its scenic fjordside setting and proximity to the Steinsdalsfossen waterfall.
- 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_69b595e7d1e481909538deb06b6007a2 |
completed | March 14, 2026, 5:07 p.m. |
Created at: March 8, 2026, 3:24 p.m.