Triple
T2005850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Store Frøen, Aker, Norway |
E43582
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Aker
Aker is a historical area and former municipality that once surrounded and included much of what is now Oslo, Norway.
|
E227158
|
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: Aker | Statement: [Store Frøen, Aker, Norway, locatedIn, Aker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aker Context triple: [Store Frøen, Aker, Norway, locatedIn, Aker]
-
A.
Kongsberg
Kongsberg is a Norwegian town known for its historic silver mines and its modern high-tech and defense industries.
-
B.
Aker Finnyards
Aker Finnyards is a Finnish shipbuilding company known for constructing various naval and commercial vessels, including advanced military ships.
-
C.
Støre
Støre is a Norwegian surname most prominently associated with Jonas Gahr Støre, the Prime Minister of Norway and leader of the Labour Party.
-
D.
Akersneset
Akersneset is a headland in central Oslo, Norway, forming part of the waterfront area that includes the historic Akershus Fortress.
-
E.
Sandefjord
Sandefjord is a coastal town and municipality in southern Norway known for its maritime heritage, whaling history, and popular seaside attractions.
- 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: Aker Triple: [Store Frøen, Aker, Norway, locatedIn, Aker]
Generated description
Aker is a historical area and former municipality that once surrounded and included much of what is now Oslo, Norway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aker Target entity description: Aker is a historical area and former municipality that once surrounded and included much of what is now Oslo, Norway.
-
A.
Kongsberg
Kongsberg is a Norwegian town known for its historic silver mines and its modern high-tech and defense industries.
-
B.
Aker Finnyards
Aker Finnyards is a Finnish shipbuilding company known for constructing various naval and commercial vessels, including advanced military ships.
-
C.
Støre
Støre is a Norwegian surname most prominently associated with Jonas Gahr Støre, the Prime Minister of Norway and leader of the Labour Party.
-
D.
Akersneset
Akersneset is a headland in central Oslo, Norway, forming part of the waterfront area that includes the historic Akershus Fortress.
-
E.
Sandefjord
Sandefjord is a coastal town and municipality in southern Norway known for its maritime heritage, whaling history, and popular seaside attractions.
- 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_69a88715dbbc8190b2299e29e955d997 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb898795481909920c1a4c4d62c2d |
completed | March 7, 2026, 5:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae0adedd388190a09361c3e69a4ed5 |
completed | March 8, 2026, 11:48 p.m. |
| NEDg | Description generation | batch_69ae0b76f0fc8190bb5f40689ee7f8fe |
completed | March 8, 2026, 11:51 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae0c586bd88190ae23e84291d2fe81 |
completed | March 8, 2026, 11:55 p.m. |
Created at: March 4, 2026, 7:37 p.m.