Triple
T15216468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bybanen |
E363648
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object |
Byparken
Byparken is the central light rail station and transit hub in downtown Bergen, Norway, serving as a key access point to the city’s urban core.
|
E1144730
|
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: Byparken | Statement: [Bybanen, terminus, Byparken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Byparken Context triple: [Bybanen, terminus, Byparken]
-
A.
Valbyparken
Valbyparken is one of Copenhagen’s largest public parks, known for its expansive green spaces, themed gardens, and recreational facilities in the Valby district.
-
B.
Pildammsparken
Pildammsparken is a large historic city park in Malmö, Sweden, known for its expansive ponds, formal gardens, and popular recreational areas.
-
C.
Kungsparken
Kungsparken is a historic and centrally located public park in Malmö, Sweden, known for its lush greenery, canals, and 19th-century landscape design.
-
D.
Näsbypark
Näsbypark is a residential suburban district in the northern Stockholm area of Sweden, known for its villas, green spaces, and coastal location by the Baltic Sea.
-
E.
In the Park
"In the Park" is a song featured on the album *Subterranean Jungle* by the American punk rock band Ramones.
- 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: Byparken Triple: [Bybanen, terminus, Byparken]
Generated description
Byparken is the central light rail station and transit hub in downtown Bergen, Norway, serving as a key access point to the city’s urban core.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Byparken Target entity description: Byparken is the central light rail station and transit hub in downtown Bergen, Norway, serving as a key access point to the city’s urban core.
-
A.
Valbyparken
Valbyparken is one of Copenhagen’s largest public parks, known for its expansive green spaces, themed gardens, and recreational facilities in the Valby district.
-
B.
Pildammsparken
Pildammsparken is a large historic city park in Malmö, Sweden, known for its expansive ponds, formal gardens, and popular recreational areas.
-
C.
Kungsparken
Kungsparken is a historic and centrally located public park in Malmö, Sweden, known for its lush greenery, canals, and 19th-century landscape design.
-
D.
Näsbypark
Näsbypark is a residential suburban district in the northern Stockholm area of Sweden, known for its villas, green spaces, and coastal location by the Baltic Sea.
-
E.
In the Park
"In the Park" is a song featured on the album *Subterranean Jungle* by the American punk rock band Ramones.
- 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_69fedd3159fc81908c05cfbd0bd7e5ac |
completed | May 9, 2026, 7:07 a.m. |
| NEDg | Description generation | batch_69fedea1fea88190b891485794acfa8d |
completed | May 9, 2026, 7:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fedf2b52348190bd8fc6999cb0abd7 |
completed | May 9, 2026, 7:15 a.m. |
Created at: April 10, 2026, 3:11 a.m.