Triple
T7853804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skedsmo |
E182120
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object |
Nittedal
Nittedal is a municipality in Viken county, Norway, known for its forested landscapes and role as a commuter area north of Oslo.
|
E701692
|
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: Nittedal | Statement: [Skedsmo, borderedBy, Nittedal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nittedal Context triple: [Skedsmo, borderedBy, Nittedal]
-
A.
Tvedestrand
Tvedestrand is a coastal town and municipality in southern Norway known for its wooden houses, maritime heritage, and picturesque archipelago.
-
B.
Lørenskog
Lørenskog is a suburban municipality in Viken county, Norway, located just east of Oslo and known for its residential areas and commercial centers.
-
C.
Slemdal
Slemdal is a residential neighborhood in the Vestre Aker borough of Oslo, Norway, known for its green surroundings and affluent character.
-
D.
Sogndal
Sogndal is a village and municipality in Vestland county, Norway, known for its scenic fjord landscape, agriculture, and as a regional education and service center.
-
E.
Steinkjer
Steinkjer is a town and municipality in central Norway that serves as an important regional center and administrative hub in Trøndelag county.
- 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: Nittedal Triple: [Skedsmo, borderedBy, Nittedal]
Generated description
Nittedal is a municipality in Viken county, Norway, known for its forested landscapes and role as a commuter area north of Oslo.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nittedal Target entity description: Nittedal is a municipality in Viken county, Norway, known for its forested landscapes and role as a commuter area north of Oslo.
-
A.
Tvedestrand
Tvedestrand is a coastal town and municipality in southern Norway known for its wooden houses, maritime heritage, and picturesque archipelago.
-
B.
Lørenskog
Lørenskog is a suburban municipality in Viken county, Norway, located just east of Oslo and known for its residential areas and commercial centers.
-
C.
Slemdal
Slemdal is a residential neighborhood in the Vestre Aker borough of Oslo, Norway, known for its green surroundings and affluent character.
-
D.
Sogndal
Sogndal is a village and municipality in Vestland county, Norway, known for its scenic fjord landscape, agriculture, and as a regional education and service center.
-
E.
Steinkjer
Steinkjer is a town and municipality in central Norway that serves as an important regional center and administrative hub in Trøndelag county.
- 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb18ed56d481909266d862e0ae152d |
completed | March 31, 2026, 12:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbdf21add88190bc07d3164e940116 |
completed | March 31, 2026, 2:50 p.m. |
| NEDg | Description generation | batch_69cbe309518481909b0857271cb27ab0 |
completed | March 31, 2026, 3:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc05e055588190a5680c4416631c32 |
completed | March 31, 2026, 5:35 p.m. |
Created at: March 30, 2026, 4:51 p.m.