Triple
T9421409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lysakerelva |
E227159
|
entity |
| Predicate | hasSource |
P409
|
FINISHED |
| Object |
Bogstadvannet
Bogstadvannet is a lake on the border of Oslo and Bærum in Norway, known for recreation, bathing, and as part of the local watercourse system.
|
E798432
|
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: Bogstadvannet | Statement: [Lysakerelva, hasSource, Bogstadvannet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bogstadvannet Context triple: [Lysakerelva, hasSource, Bogstadvannet]
-
A.
Dovrebanen
Dovrebanen is a major Norwegian railway line connecting Oslo and Trondheim across the Dovrefjell mountain area.
-
B.
Bogen i Ofoten
Bogen i Ofoten is a small coastal village in Nordland county, Norway, known for its scenic fjord landscape and location on the island of Hinnøya.
-
C.
Blåränderna
Blåränderna is a popular nickname for Djurgårdens IF, referring to the Swedish sports club’s iconic blue-striped team colors.
-
D.
Gavlerinken
Gavlerinken is the former name of Monitor ERP Arena, an indoor ice hockey and events venue in Gävle, Sweden.
-
E.
Bøler
Bøler is a residential neighborhood in the Østensjø borough of Oslo, Norway, known for its post-war apartment blocks, green surroundings, and access to the Østmarka forest.
- 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: Bogstadvannet Triple: [Lysakerelva, hasSource, Bogstadvannet]
Generated description
Bogstadvannet is a lake on the border of Oslo and Bærum in Norway, known for recreation, bathing, and as part of the local watercourse system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bogstadvannet Target entity description: Bogstadvannet is a lake on the border of Oslo and Bærum in Norway, known for recreation, bathing, and as part of the local watercourse system.
-
A.
Dovrebanen
Dovrebanen is a major Norwegian railway line connecting Oslo and Trondheim across the Dovrefjell mountain area.
-
B.
Bogen i Ofoten
Bogen i Ofoten is a small coastal village in Nordland county, Norway, known for its scenic fjord landscape and location on the island of Hinnøya.
-
C.
Blåränderna
Blåränderna is a popular nickname for Djurgårdens IF, referring to the Swedish sports club’s iconic blue-striped team colors.
-
D.
Gavlerinken
Gavlerinken is the former name of Monitor ERP Arena, an indoor ice hockey and events venue in Gävle, Sweden.
-
E.
Bøler
Bøler is a residential neighborhood in the Østensjø borough of Oslo, Norway, known for its post-war apartment blocks, green surroundings, and access to the Østmarka forest.
- 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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd6c2651c48190808281779fab49df |
completed | April 1, 2026, 7:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d107c95c9481909957b99cacf5e045 |
completed | April 4, 2026, 12:44 p.m. |
| NEDg | Description generation | batch_69d1085a980c8190b4c6d811b07ab180 |
completed | April 4, 2026, 12:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1093f440481909aa27287019191ac |
completed | April 4, 2026, 12:51 p.m. |
Created at: March 30, 2026, 7:48 p.m.