Triple
T2965470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vesterålen |
E80150
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Bø
Bø is a coastal municipality in Nordland county, Norway, known for its dramatic landscapes, fishing heritage, and location within the Vesterålen archipelago.
|
E315255
|
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: Bø | Statement: [Vesterålen, hasMunicipality, Bø]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bø Context triple: [Vesterålen, hasMunicipality, Bø]
-
A.
Bojnord
Bojnord is a city in northeastern Iran that serves as the capital of North Khorasan Province.
-
B.
Dombås
Dombås is a village in central Norway that serves as an important road and rail junction in the Gudbrandsdalen region and was a notable site of fighting during World War II.
-
C.
Brevik
Brevik is a locality within Tyresö Municipality in Stockholm County, Sweden, known for its coastal residential areas and proximity to the Stockholm archipelago.
-
D.
Sandefjord
Sandefjord is a coastal town and municipality in southern Norway known for its maritime heritage, whaling history, and popular seaside attractions.
-
E.
Bærum
Bærum is a wealthy suburban municipality just west of Oslo, Norway, known for its high standard of living and residential communities.
- 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: Bø Triple: [Vesterålen, hasMunicipality, Bø]
Generated description
Bø is a coastal municipality in Nordland county, Norway, known for its dramatic landscapes, fishing heritage, and location within the Vesterålen archipelago.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bø Target entity description: Bø is a coastal municipality in Nordland county, Norway, known for its dramatic landscapes, fishing heritage, and location within the Vesterålen archipelago.
-
A.
Bojnord
Bojnord is a city in northeastern Iran that serves as the capital of North Khorasan Province.
-
B.
Dombås
Dombås is a village in central Norway that serves as an important road and rail junction in the Gudbrandsdalen region and was a notable site of fighting during World War II.
-
C.
Brevik
Brevik is a locality within Tyresö Municipality in Stockholm County, Sweden, known for its coastal residential areas and proximity to the Stockholm archipelago.
-
D.
Sandefjord
Sandefjord is a coastal town and municipality in southern Norway known for its maritime heritage, whaling history, and popular seaside attractions.
-
E.
Bærum
Bærum is a wealthy suburban municipality just west of Oslo, Norway, known for its high standard of living and residential communities.
- 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_69ad8b1341848190bd19dbf46892887d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad995a28e88190a4d6b9ef2c0d8e61 |
completed | March 8, 2026, 3:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0fc9bc190819087cb35ee7c78825a |
completed | March 11, 2026, 5:24 a.m. |
| NEDg | Description generation | batch_69b0fd25e07c819088b2b1bcef4cf54e |
completed | March 11, 2026, 5:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b100ecbee081908832ddec0efdc751 |
completed | March 11, 2026, 5:43 a.m. |
Created at: March 8, 2026, 2:58 p.m.