Triple
T3648596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karmøy |
E77362
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Åkrehamn
Åkrehamn is a coastal town in southwestern Norway known for its fishing industry and scenic North Sea shoreline.
|
E413537
|
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: Åkrehamn | Statement: [Karmøy, hasTown, Åkrehamn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Åkrehamn Context triple: [Karmøy, hasTown, Åkrehamn]
-
A.
Haugesund
Haugesund is a coastal city in southwestern Norway known for its maritime heritage, shipbuilding industry, and annual film and jazz festivals.
-
B.
Bardufoss
Bardufoss is a town in northern Norway known for its military base, including the main headquarters of the Norwegian Army in the region, and its nearby airport.
-
C.
Nordfjordeid
Nordfjordeid is a village in western Norway known as a regional center in Nordfjord and the birthplace of mathematician Sophus Lie.
-
D.
Kragerø
Kragerø is a coastal town in Norway renowned for its picturesque archipelago, historic wooden buildings, and role as a popular summer holiday destination.
-
E.
Askøy
Askøy is a large island and municipality on Norway’s west coast, situated near Bergen and known for its coastal landscapes and commuter links to the city.
- 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: Åkrehamn Triple: [Karmøy, hasTown, Åkrehamn]
Generated description
Åkrehamn is a coastal town in southwestern Norway known for its fishing industry and scenic North Sea shoreline.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Åkrehamn Target entity description: Åkrehamn is a coastal town in southwestern Norway known for its fishing industry and scenic North Sea shoreline.
-
A.
Haugesund
Haugesund is a coastal city in southwestern Norway known for its maritime heritage, shipbuilding industry, and annual film and jazz festivals.
-
B.
Bardufoss
Bardufoss is a town in northern Norway known for its military base, including the main headquarters of the Norwegian Army in the region, and its nearby airport.
-
C.
Nordfjordeid
Nordfjordeid is a village in western Norway known as a regional center in Nordfjord and the birthplace of mathematician Sophus Lie.
-
D.
Kragerø
Kragerø is a coastal town in Norway renowned for its picturesque archipelago, historic wooden buildings, and role as a popular summer holiday destination.
-
E.
Askøy
Askøy is a large island and municipality on Norway’s west coast, situated near Bergen and known for its coastal landscapes and commuter links to the city.
- 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_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_69b56b316140819089c90f3e2bd81ad8 |
completed | March 14, 2026, 2:05 p.m. |
| NEDg | Description generation | batch_69b56f05a6d48190a5bf5b5279134dc8 |
completed | March 14, 2026, 2:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b56f5253c88190baef7397d60aa300 |
completed | March 14, 2026, 2:23 p.m. |
Created at: March 8, 2026, 3:24 p.m.