Triple
T7448700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kjelsås |
E171949
|
entity |
| Predicate | hasSportsClub |
P346
|
FINISHED |
| Object |
Kjelsås IL
Kjelsås IL is a Norwegian multi-sport club based in the Kjelsås neighborhood of Oslo, known for activities such as football, handball, and skiing.
|
E665910
|
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: Kjelsås IL | Statement: [Kjelsås, hasSportsClub, Kjelsås IL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kjelsås IL Context triple: [Kjelsås, hasSportsClub, Kjelsås IL]
-
A.
Tromsø IL
Tromsø IL is a Norwegian professional football club based in the city of Tromsø, known for competing in the country’s top divisions and for being one of the world’s northernmost elite clubs.
-
B.
Vålerenga
Vålerenga is a neighborhood in Oslo, Norway, known for its working-class roots and strong association with the local football club Vålerenga Fotball.
-
C.
Lørenskog IF
Lørenskog IF is a Norwegian sports club best known for its football team, based in Lørenskog near Oslo.
-
D.
Lillehammer FK
Lillehammer FK is a Norwegian football club based in the town of Lillehammer, competing in the lower tiers of the national league system.
-
E.
Mjøndalen
Mjøndalen is a town in Viken county, Norway, known historically for its industry and for its football club Mjøndalen IF.
- 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: Kjelsås IL Triple: [Kjelsås, hasSportsClub, Kjelsås IL]
Generated description
Kjelsås IL is a Norwegian multi-sport club based in the Kjelsås neighborhood of Oslo, known for activities such as football, handball, and skiing.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kjelsås IL Target entity description: Kjelsås IL is a Norwegian multi-sport club based in the Kjelsås neighborhood of Oslo, known for activities such as football, handball, and skiing.
-
A.
Tromsø IL
Tromsø IL is a Norwegian professional football club based in the city of Tromsø, known for competing in the country’s top divisions and for being one of the world’s northernmost elite clubs.
-
B.
Vålerenga
Vålerenga is a neighborhood in Oslo, Norway, known for its working-class roots and strong association with the local football club Vålerenga Fotball.
-
C.
Lørenskog IF
Lørenskog IF is a Norwegian sports club best known for its football team, based in Lørenskog near Oslo.
-
D.
Lillehammer FK
Lillehammer FK is a Norwegian football club based in the town of Lillehammer, competing in the lower tiers of the national league system.
-
E.
Mjøndalen
Mjøndalen is a town in Viken county, Norway, known historically for its industry and for its football club Mjøndalen IF.
- 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_69c68a65402881908f7869368eb746fb |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f389ddd48190a4b8753c67220c4f |
completed | March 27, 2026, 9:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c827b0e9848190b28ff10b12b10a33 |
completed | March 28, 2026, 7:10 p.m. |
| NEDg | Description generation | batch_69c8299bb8c08190a5a78b0c1a8cc0fb |
completed | March 28, 2026, 7:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c82ad4384481909616bdfd02624a48 |
completed | March 28, 2026, 7:24 p.m. |
Created at: March 27, 2026, 3:14 p.m.