Triple
T19555419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brandbu |
E489295
|
entity |
| Predicate | hasFormerRailwayStation |
P28717
|
FINISHED |
| Object |
Brandbu Station
Brandbu Station was a former railway stop in Brandbu, Norway, that once served as a local transport hub before its closure.
|
E1384009
|
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: Brandbu Station | Statement: [Brandbu, hasFormerRailwayStation, Brandbu Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brandbu Station Context triple: [Brandbu, hasFormerRailwayStation, Brandbu Station]
-
A.
Bleiken Station
Bleiken Station is a local railway stop serving the village of Bleiken in the municipality of Gran, Norway.
-
B.
Vinstra Station
Vinstra Station is a railway station in the town of Vinstra in Innlandet county, Norway, serving as a stop on the Dovre Line.
-
C.
Teine Station
Teine Station is a key railway station in Sapporo, Hokkaido, Japan, serving as an important hub for local and regional train services.
-
D.
Rommen station
Rommen station is a metro stop in Oslo, Norway, located in the Groruddalen area and integrated into the city's rapid transit network.
-
E.
Wende station
Wende station is a metro station on Taipei's Wenhu (Brown) Line serving the Neihu District in Taiwan.
- 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: Brandbu Station Triple: [Brandbu, hasFormerRailwayStation, Brandbu Station]
Generated description
Brandbu Station was a former railway stop in Brandbu, Norway, that once served as a local transport hub before its closure.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brandbu Station Target entity description: Brandbu Station was a former railway stop in Brandbu, Norway, that once served as a local transport hub before its closure.
-
A.
Bleiken Station
Bleiken Station is a local railway stop serving the village of Bleiken in the municipality of Gran, Norway.
-
B.
Vinstra Station
Vinstra Station is a railway station in the town of Vinstra in Innlandet county, Norway, serving as a stop on the Dovre Line.
-
C.
Teine Station
Teine Station is a key railway station in Sapporo, Hokkaido, Japan, serving as an important hub for local and regional train services.
-
D.
Rommen station
Rommen station is a metro stop in Oslo, Norway, located in the Groruddalen area and integrated into the city's rapid transit network.
-
E.
Wende station
Wende station is a metro station on Taipei's Wenhu (Brown) Line serving the Neihu District in Taiwan.
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63d335f888190abfc5ba974d3c65e |
completed | April 20, 2026, 2:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07577e66c4819080298e223c2ece16 |
completed | May 15, 2026, 5:27 p.m. |
| NEDg | Description generation | batch_6a07583fc26481908bd2f00c19f3b4cd |
completed | May 15, 2026, 5:30 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07594a23ac81908807df4605555d3f |
completed | May 15, 2026, 5:35 p.m. |
Created at: April 10, 2026, 1:42 p.m.