Triple
T895821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonas Gahr Støre |
E19343
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Støre
Støre is a Norwegian surname most prominently associated with Jonas Gahr Støre, the Prime Minister of Norway and leader of the Labour Party.
|
E149736
|
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: Støre | Statement: [Jonas Gahr Støre, familyName, Støre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Støre Context triple: [Jonas Gahr Støre, familyName, Støre]
-
A.
Sandefjord
Sandefjord is a coastal town and municipality in southern Norway known for its maritime heritage, whaling history, and popular seaside attractions.
-
B.
Tøyen
Tøyen is a neighborhood in Oslo, Norway, known for its cultural institutions, parks, and educational facilities.
-
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.
Drammen
Drammen is a city and municipality in southeastern Norway known for its riverside setting along the Drammenselva and its role as a regional commercial and transport hub.
-
E.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
- 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: Støre Triple: [Jonas Gahr Støre, familyName, Støre]
Generated description
Støre is a Norwegian surname most prominently associated with Jonas Gahr Støre, the Prime Minister of Norway and leader of the Labour Party.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Støre Target entity description: Støre is a Norwegian surname most prominently associated with Jonas Gahr Støre, the Prime Minister of Norway and leader of the Labour Party.
-
A.
Sandefjord
Sandefjord is a coastal town and municipality in southern Norway known for its maritime heritage, whaling history, and popular seaside attractions.
-
B.
Tøyen
Tøyen is a neighborhood in Oslo, Norway, known for its cultural institutions, parks, and educational facilities.
-
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.
Drammen
Drammen is a city and municipality in southeastern Norway known for its riverside setting along the Drammenselva and its role as a regional commercial and transport hub.
-
E.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
- 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_69a4939d37188190848be3d426ebc9ae |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad23d6e88190a2fb5e1e168a7b44 |
completed | March 1, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acbad10ae48190af7dcaa8dfff30ec |
completed | March 7, 2026, 11:54 p.m. |
| NEDg | Description generation | batch_69acbb3ebf4c8190bebb55ac052cd6e3 |
completed | March 7, 2026, 11:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69acbbc2729c819091e7d683b73baaf7 |
completed | March 7, 2026, 11:58 p.m. |
Created at: March 1, 2026, 7:39 p.m.