Triple
T14056727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M1 (Copenhagen Metro) |
E338237
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Sundby station
Sundby station is an elevated Copenhagen Metro station on the M1 line serving the Amager district of Copenhagen, Denmark.
|
E1096236
|
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: Sundby station | Statement: [M1 (Copenhagen Metro), hasStation, Sundby station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sundby station Context triple: [M1 (Copenhagen Metro), hasStation, Sundby station]
-
A.
Fasanvej Station
Fasanvej Station is a Copenhagen Metro station serving the Frederiksberg district of Copenhagen, Denmark.
-
B.
Flintholm station
Flintholm station is a major Copenhagen transport hub that serves both the Metro and S-train networks, facilitating easy transfers between multiple lines.
-
C.
Vanløse station
Vanløse station is a major public transport hub in Copenhagen that serves as an interchange between the S-train network and the Copenhagen Metro.
-
D.
Lindevang Station
Lindevang Station is a Copenhagen Metro station serving the Frederiksberg district of Copenhagen, Denmark.
-
E.
Henriksdal station
Henriksdal station is a commuter rail stop in the Stockholm area that serves passengers on the Saltsjöbanan 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: Sundby station Triple: [M1 (Copenhagen Metro), hasStation, Sundby station]
Generated description
Sundby station is an elevated Copenhagen Metro station on the M1 line serving the Amager district of Copenhagen, Denmark.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sundby station Target entity description: Sundby station is an elevated Copenhagen Metro station on the M1 line serving the Amager district of Copenhagen, Denmark.
-
A.
Fasanvej Station
Fasanvej Station is a Copenhagen Metro station serving the Frederiksberg district of Copenhagen, Denmark.
-
B.
Flintholm station
Flintholm station is a major Copenhagen transport hub that serves both the Metro and S-train networks, facilitating easy transfers between multiple lines.
-
C.
Vanløse station
Vanløse station is a major public transport hub in Copenhagen that serves as an interchange between the S-train network and the Copenhagen Metro.
-
D.
Lindevang Station
Lindevang Station is a Copenhagen Metro station serving the Frederiksberg district of Copenhagen, Denmark.
-
E.
Henriksdal station
Henriksdal station is a commuter rail stop in the Stockholm area that serves passengers on the Saltsjöbanan 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de3c8e6d008190af8892f34c5cefbd |
completed | April 14, 2026, 1:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c255d8c81908bdac0a28718563e |
completed | May 8, 2026, 2:36 a.m. |
| NEDg | Description generation | batch_69fd503e7b8c8190bd67e5173c3a36b1 |
completed | May 8, 2026, 2:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd50cd88748190904ad67a8a20c48c |
completed | May 8, 2026, 2:56 a.m. |
Created at: April 9, 2026, 10:20 p.m.