Triple
T9552190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Svein Stølen |
E230448
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Stølen
Stølen is a Norwegian surname most notably associated with physicist and University of Oslo rector Svein Stølen.
|
E807010
|
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: Stølen | Statement: [Svein Stølen, familyName, Stølen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stølen Context triple: [Svein Stølen, familyName, Stølen]
-
A.
Storlien
Storlien is a village and ski resort in central Sweden near the Norwegian border, known for its winter sports and cross-border rail connections.
-
B.
Skjetten
Skjetten is a suburban residential area in Lillestrøm municipality in Viken county, Norway, located northeast of Oslo.
-
C.
Storslett
Storslett is a small village and administrative center in Nordreisa Municipality in Troms og Finnmark county in northern Norway.
-
D.
Støren
Støren is a village in Trøndelag county, Norway, serving as a local commercial and transportation hub in the Gauldalen valley.
-
E.
Dovrebanen
Dovrebanen is a major Norwegian railway line connecting Oslo and Trondheim across the Dovrefjell mountain area.
- 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: Stølen Triple: [Svein Stølen, familyName, Stølen]
Generated description
Stølen is a Norwegian surname most notably associated with physicist and University of Oslo rector Svein Stølen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stølen Target entity description: Stølen is a Norwegian surname most notably associated with physicist and University of Oslo rector Svein Stølen.
-
A.
Storlien
Storlien is a village and ski resort in central Sweden near the Norwegian border, known for its winter sports and cross-border rail connections.
-
B.
Skjetten
Skjetten is a suburban residential area in Lillestrøm municipality in Viken county, Norway, located northeast of Oslo.
-
C.
Storslett
Storslett is a small village and administrative center in Nordreisa Municipality in Troms og Finnmark county in northern Norway.
-
D.
Støren
Støren is a village in Trøndelag county, Norway, serving as a local commercial and transportation hub in the Gauldalen valley.
-
E.
Dovrebanen
Dovrebanen is a major Norwegian railway line connecting Oslo and Trondheim across the Dovrefjell mountain area.
- 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_69ca847d3be8819099c9dad2a7e786f1 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd991f87e48190b5a5f4b3dfe7c1dd |
completed | April 1, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d15286f7c881909258b9f06a81e464 |
completed | April 4, 2026, 6:03 p.m. |
| NEDg | Description generation | batch_69d154e80dc081909af88042ef0bebce |
completed | April 4, 2026, 6:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d155977ab481908951906946b74248 |
completed | April 4, 2026, 6:16 p.m. |
Created at: March 30, 2026, 8:02 p.m.