Triple
T10427866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lillestrøm (municipality) |
E245831
|
entity |
| Predicate | hasMayor |
P185
|
FINISHED |
| Object |
Jørgen Vik
Jørgen Vik is a Norwegian politician who serves as the mayor of the municipality of Lillestrøm.
|
E875776
|
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: Jørgen Vik | Statement: [Lillestrøm (municipality), hasMayor, Jørgen Vik]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jørgen Vik Context triple: [Lillestrøm (municipality), hasMayor, Jørgen Vik]
-
A.
Terje Hansen
Terje Hansen is an academic author known for co-authoring scholarly work with prominent economist and mathematician Herbert Scarf.
-
B.
Jørgen Løvland
Jørgen Løvland was a Norwegian statesman and educator who served as Prime Minister and held several key ministerial posts during the early years of Norway’s independence.
-
C.
Bjørn Kjos
Bjørn Kjos is a Norwegian businessman, lawyer, and former fighter pilot best known as the co-founder and long-time CEO of the low-cost airline Norwegian Air Shuttle.
-
D.
Arvid Bjerke
Arvid Bjerke was a Swedish architect known for his significant contributions to early 20th-century architecture in Gothenburg.
-
E.
Jørgen Moe
Jørgen Moe was a Norwegian bishop, poet, and folklorist best known for co-collecting and publishing Norwegian folk tales with Peter Christen Asbjørnsen.
- 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: Jørgen Vik Triple: [Lillestrøm (municipality), hasMayor, Jørgen Vik]
Generated description
Jørgen Vik is a Norwegian politician who serves as the mayor of the municipality of Lillestrøm.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jørgen Vik Target entity description: Jørgen Vik is a Norwegian politician who serves as the mayor of the municipality of Lillestrøm.
-
A.
Terje Hansen
Terje Hansen is an academic author known for co-authoring scholarly work with prominent economist and mathematician Herbert Scarf.
-
B.
Jørgen Løvland
Jørgen Løvland was a Norwegian statesman and educator who served as Prime Minister and held several key ministerial posts during the early years of Norway’s independence.
-
C.
Bjørn Kjos
Bjørn Kjos is a Norwegian businessman, lawyer, and former fighter pilot best known as the co-founder and long-time CEO of the low-cost airline Norwegian Air Shuttle.
-
D.
Arvid Bjerke
Arvid Bjerke was a Swedish architect known for his significant contributions to early 20th-century architecture in Gothenburg.
-
E.
Jørgen Moe
Jørgen Moe was a Norwegian bishop, poet, and folklorist best known for co-collecting and publishing Norwegian folk tales with Peter Christen Asbjørnsen.
- 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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea4a7dcc81909a830e08656a1c0c |
completed | April 7, 2026, 11:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96b2803d88190ab93dd19b4cfee30 |
completed | April 10, 2026, 9:27 p.m. |
| NEDg | Description generation | batch_69d96dee84f48190bf5b0cb1115a8bba |
completed | April 10, 2026, 9:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d9708824208190acf75933962d690f |
completed | April 10, 2026, 9:50 p.m. |
Created at: April 6, 2026, 12:13 p.m.