Triple
T2934358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Averøya |
E79229
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Bremsnes
Bremsnes is a village on the island of Averøya in Møre og Romsdal county, Norway, known for its coastal setting and local church.
|
E316580
|
NE FINISHED |
How this triple was built (4 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: Bremsnes | Statement: [Averøya, hasSettlement, Bremsnes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bremsnes Context triple: [Averøya, hasSettlement, Bremsnes]
-
A.
Bolnes
Bolnes is a Dutch surname most notably associated with Catharina Bolnes, the wife of painter Johannes Vermeer.
-
B.
Brevik
Brevik is a locality within Tyresö Municipality in Stockholm County, Sweden, known for its coastal residential areas and proximity to the Stockholm archipelago.
-
C.
Kragerø
Kragerø is a coastal town in Norway renowned for its picturesque archipelago, historic wooden buildings, and role as a popular summer holiday 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.
Bjørvika
Bjørvika is a waterfront neighborhood in central Oslo, Norway, known for its modern architecture and cultural institutions such as the Munch Museum and the Oslo Opera House.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bremsnes Triple: [Averøya, hasSettlement, Bremsnes]
Generated description
Bremsnes is a village on the island of Averøya in Møre og Romsdal county, Norway, known for its coastal setting and local church.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bremsnes Target entity description: Bremsnes is a village on the island of Averøya in Møre og Romsdal county, Norway, known for its coastal setting and local church.
-
A.
Bolnes
Bolnes is a Dutch surname most notably associated with Catharina Bolnes, the wife of painter Johannes Vermeer.
-
B.
Brevik
Brevik is a locality within Tyresö Municipality in Stockholm County, Sweden, known for its coastal residential areas and proximity to the Stockholm archipelago.
-
C.
Kragerø
Kragerø is a coastal town in Norway renowned for its picturesque archipelago, historic wooden buildings, and role as a popular summer holiday 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.
Bjørvika
Bjørvika is a waterfront neighborhood in central Oslo, Norway, known for its modern architecture and cultural institutions such as the Munch Museum and the Oslo Opera House.
- F. None of above. chosen
Provenance (5 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_69ad8b0fbab081908f6a61567c045d8d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad983b65f881909b8b7d3dc5c224fd |
completed | March 8, 2026, 3:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b108d4e5408190a0dd3728c5cf6a47 |
completed | March 11, 2026, 6:16 a.m. |
| NEDg | Description generation | batch_69b10ccadf608190b2032ebb51271c90 |
completed | March 11, 2026, 6:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b10d3e846481909a4342d844071040 |
completed | March 11, 2026, 6:35 a.m. |
Created at: March 8, 2026, 2:56 p.m.