Triple
T1047314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vålerenga Fotball |
E22610
|
entity |
| Predicate | locatedInDistrict |
P40
|
FINISHED |
| Object |
Vålerenga
Vålerenga is a neighborhood in Oslo, Norway, known for its working-class roots and strong association with the local football club Vålerenga Fotball.
|
E124539
|
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: Vålerenga | Statement: [Vålerenga Fotball, locatedInDistrict, Vålerenga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vålerenga Context triple: [Vålerenga Fotball, locatedInDistrict, Vålerenga]
-
A.
Vålerenga Fotball
Vålerenga Fotball is a Norwegian professional football club based in Oslo, known for its passionate fan base and history in the country’s top division.
-
B.
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.
-
C.
Kvik Halden FK
Kvik Halden FK is a Norwegian football club based in the town of Halden, known for competing in the national league system.
-
D.
Lørenskog IF
Lørenskog IF is a Norwegian sports club best known for its football team, based in Lørenskog near Oslo.
-
E.
Lillehammer IK
Lillehammer IK is a Norwegian ice hockey club based in Lillehammer that competes in the country’s top leagues.
- 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: Vålerenga Triple: [Vålerenga Fotball, locatedInDistrict, Vålerenga]
Generated description
Vålerenga is a neighborhood in Oslo, Norway, known for its working-class roots and strong association with the local football club Vålerenga Fotball.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vålerenga Target entity description: Vålerenga is a neighborhood in Oslo, Norway, known for its working-class roots and strong association with the local football club Vålerenga Fotball.
-
A.
Vålerenga Fotball
Vålerenga Fotball is a Norwegian professional football club based in Oslo, known for its passionate fan base and history in the country’s top division.
-
B.
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.
-
C.
Kvik Halden FK
Kvik Halden FK is a Norwegian football club based in the town of Halden, known for competing in the national league system.
-
D.
Lørenskog IF
Lørenskog IF is a Norwegian sports club best known for its football team, based in Lørenskog near Oslo.
-
E.
Lillehammer IK
Lillehammer IK is a Norwegian ice hockey club based in Lillehammer that competes in the country’s top leagues.
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b84d30888190b66f7245d781957d |
completed | March 1, 2026, 10:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac429cc3c481909c55459790d6857f |
completed | March 7, 2026, 3:22 p.m. |
| NEDg | Description generation | batch_69ac4394156881909042176e035414be |
completed | March 7, 2026, 3:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac43ded4308190bbedda3e2c6255a4 |
completed | March 7, 2026, 3:27 p.m. |
Created at: March 1, 2026, 7:42 p.m.