Triple
T7394608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oslo Metro Line 1 |
E170589
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Brynseng station
Brynseng station is a metro station in Oslo, Norway, serving as an interchange point on the Oslo Metro network.
|
E681310
|
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: Brynseng station | Statement: [Oslo Metro Line 1, hasStation, Brynseng station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brynseng station Context triple: [Oslo Metro Line 1, hasStation, Brynseng station]
-
A.
Mortensrud station
Mortensrud station is a metro station in Oslo, Norway, serving as the southern terminus of the Oslo Metro’s Line 3 in the Mortensrud neighborhood.
-
B.
Ulsrud station
Ulsrud station is a metro station on the Oslo Metro network in Norway, serving the residential area of Ulsrud in the Østensjø borough.
-
C.
Skøyen Station
Skøyen Station is a major railway and commuter hub in Oslo, Norway, serving regional and local trains as part of the city's western transport corridor.
-
D.
Tøyen station
Tøyen station is an Oslo Metro station in the Tøyen neighborhood of Oslo, Norway, serving as a stop on the system’s Ring Line.
-
E.
Vegårshei Station
Vegårshei Station is a railway station in Vegårshei, Norway, serving as a local stop on the Sørlandet Line.
- 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: Brynseng station Triple: [Oslo Metro Line 1, hasStation, Brynseng station]
Generated description
Brynseng station is a metro station in Oslo, Norway, serving as an interchange point on the Oslo Metro network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brynseng station Target entity description: Brynseng station is a metro station in Oslo, Norway, serving as an interchange point on the Oslo Metro network.
-
A.
Mortensrud station
Mortensrud station is a metro station in Oslo, Norway, serving as the southern terminus of the Oslo Metro’s Line 3 in the Mortensrud neighborhood.
-
B.
Ulsrud station
Ulsrud station is a metro station on the Oslo Metro network in Norway, serving the residential area of Ulsrud in the Østensjø borough.
-
C.
Skøyen Station
Skøyen Station is a major railway and commuter hub in Oslo, Norway, serving regional and local trains as part of the city's western transport corridor.
-
D.
Tøyen station
Tøyen station is an Oslo Metro station in the Tøyen neighborhood of Oslo, Norway, serving as a stop on the system’s Ring Line.
-
E.
Vegårshei Station
Vegårshei Station is a railway station in Vegårshei, Norway, serving as a local stop on the Sørlandet Line.
- 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_69c68a5f04188190ac266569c9280347 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2279de4819081b8876d02f55388 |
completed | March 27, 2026, 9:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8a201e73081908cbe64f351e36f77 |
completed | March 29, 2026, 3:52 a.m. |
| NEDg | Description generation | batch_69c8a3a3cc2081909a5a2041cbdbe04f |
completed | March 29, 2026, 3:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8a4257d9c8190a6b13bc9d5491476 |
completed | March 29, 2026, 4:01 a.m. |
Created at: March 27, 2026, 3:09 p.m.