Triple
T15216472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bybanen |
E363648
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object |
Rådal
Rådal is a suburban area in Bergen, Norway, known as a residential and commercial district served by the city’s light rail system.
|
E1150396
|
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: Rådal | Statement: [Bybanen, terminus, Rådal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rådal Context triple: [Bybanen, terminus, Rådal]
-
A.
Mortensrud
Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
-
B.
Brårud
Brårud is a small village located within the municipality of Nes in Akershus county, Norway.
-
C.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
D.
Steinråa
Steinråa is a small settlement located in Nannestad municipality in Viken county, Norway.
-
E.
Tyssedal
Tyssedal is a small industrial village in Vestland county, Norway, known for its historic hydropower facilities and scenic location by the Sørfjorden.
- 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: Rådal Triple: [Bybanen, terminus, Rådal]
Generated description
Rådal is a suburban area in Bergen, Norway, known as a residential and commercial district served by the city’s light rail system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rådal Target entity description: Rådal is a suburban area in Bergen, Norway, known as a residential and commercial district served by the city’s light rail system.
-
A.
Mortensrud
Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
-
B.
Brårud
Brårud is a small village located within the municipality of Nes in Akershus county, Norway.
-
C.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
D.
Steinråa
Steinråa is a small settlement located in Nannestad municipality in Viken county, Norway.
-
E.
Tyssedal
Tyssedal is a small industrial village in Vestland county, Norway, known for its historic hydropower facilities and scenic location by the Sørfjorden.
- 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0076f90c481909989befe031a2cae |
completed | April 15, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef88f8ac881908ca32de44b5aa53a |
completed | May 9, 2026, 9:04 a.m. |
| NEDg | Description generation | batch_69fefce7de4881909bed29d98e4c82ce |
completed | May 9, 2026, 9:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fefdaebcf481909bddf548508e32ba |
completed | May 9, 2026, 9:26 a.m. |
Created at: April 10, 2026, 3:11 a.m.