Triple
T6083401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stovner district |
E135576
|
entity |
| Predicate | hasNeighbouringBorough |
P16160
|
FINISHED |
| Object |
Grorud
Grorud is a borough in the northeastern part of Oslo, Norway, known for its residential areas, green spaces, and diverse population.
|
E587477
|
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: Grorud | Statement: [Stovner district, hasNeighbouringBorough, Grorud]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grorud Context triple: [Stovner district, hasNeighbouringBorough, Grorud]
-
A.
Sandvika
Sandvika is a town in southeastern Norway that serves as the administrative center of Bærum and a commercial hub in the Greater Oslo Region.
-
B.
Rakkestad
Rakkestad is a rural municipality in Viken county, southeastern Norway, known for its agriculture and forests.
-
C.
Grebbestad
Grebbestad is a coastal fishing village and popular tourist destination in Tanum Municipality on Sweden’s west coast, known for its seafood and picturesque archipelago.
-
D.
Eidskog
Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
-
E.
Ulriksdal
Ulriksdal is a district in Solna, Sweden, known for the historic Ulriksdal Palace and its surrounding parklands along the Edsviken inlet.
- 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: Grorud Triple: [Stovner district, hasNeighbouringBorough, Grorud]
Generated description
Grorud is a borough in the northeastern part of Oslo, Norway, known for its residential areas, green spaces, and diverse population.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Grorud Target entity description: Grorud is a borough in the northeastern part of Oslo, Norway, known for its residential areas, green spaces, and diverse population.
-
A.
Sandvika
Sandvika is a town in southeastern Norway that serves as the administrative center of Bærum and a commercial hub in the Greater Oslo Region.
-
B.
Rakkestad
Rakkestad is a rural municipality in Viken county, southeastern Norway, known for its agriculture and forests.
-
C.
Grebbestad
Grebbestad is a coastal fishing village and popular tourist destination in Tanum Municipality on Sweden’s west coast, known for its seafood and picturesque archipelago.
-
D.
Eidskog
Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
-
E.
Ulriksdal
Ulriksdal is a district in Solna, Sweden, known for the historic Ulriksdal Palace and its surrounding parklands along the Edsviken inlet.
- 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_69c0087ad31c8190ab936e0ff28614b6 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05786233c81909010a6c2f7e7dfda |
completed | March 22, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c62cfca10c8190b9e0691ba90fff02 |
completed | March 27, 2026, 7:08 a.m. |
| NEDg | Description generation | batch_69c62dcb9e1481909fb357f2b010bc19 |
completed | March 27, 2026, 7:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c62e33354481908a6a9af5c245f307 |
completed | March 27, 2026, 7:13 a.m. |
Created at: March 22, 2026, 4:11 p.m.