Triple
T18597363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aarhus Letbane |
E454525
|
entity |
| Predicate | hasDepot |
P2413
|
FINISHED |
| Object |
Lystrup depot
Lystrup depot is the main maintenance and operations facility serving the Aarhus Letbane light rail system in Denmark.
|
E1333033
|
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: Lystrup depot | Statement: [Aarhus Letbane, hasDepot, Lystrup depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lystrup depot Context triple: [Aarhus Letbane, hasDepot, Lystrup depot]
-
A.
Roskilde Station
Roskilde Station is the main railway station serving the historic city of Roskilde in Denmark, functioning as a key regional and intercity transport hub.
-
B.
Hammarby depot
Hammarby depot is a maintenance and storage facility serving Stockholm’s Tvärbanan light rail system.
-
C.
Grefsen tram depot
Grefsen tram depot is a major maintenance and storage facility for Oslo’s tram network, serving as one of the key operational hubs for the city’s trams.
-
D.
Strømmen Station
Strømmen Station is a railway station serving the town of Strømmen in Viken county, Norway, on the Oslo commuter rail network.
-
E.
Gilleleje Station
Gilleleje Station is a railway station in the coastal town of Gilleleje in North Zealand, Denmark, serving as a key local transport hub on regional rail services.
- 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: Lystrup depot Triple: [Aarhus Letbane, hasDepot, Lystrup depot]
Generated description
Lystrup depot is the main maintenance and operations facility serving the Aarhus Letbane light rail system in Denmark.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lystrup depot Target entity description: Lystrup depot is the main maintenance and operations facility serving the Aarhus Letbane light rail system in Denmark.
-
A.
Roskilde Station
Roskilde Station is the main railway station serving the historic city of Roskilde in Denmark, functioning as a key regional and intercity transport hub.
-
B.
Hammarby depot
Hammarby depot is a maintenance and storage facility serving Stockholm’s Tvärbanan light rail system.
-
C.
Grefsen tram depot
Grefsen tram depot is a major maintenance and storage facility for Oslo’s tram network, serving as one of the key operational hubs for the city’s trams.
-
D.
Strømmen Station
Strømmen Station is a railway station serving the town of Strømmen in Viken county, Norway, on the Oslo commuter rail network.
-
E.
Gilleleje Station
Gilleleje Station is a railway station in the coastal town of Gilleleje in North Zealand, Denmark, serving as a key local transport hub on regional rail services.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5474d934481909b4afd5ef9031c73 |
completed | April 19, 2026, 9:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05037eda788190977fcb50aa4d2357 |
completed | May 13, 2026, 11:04 p.m. |
| NEDg | Description generation | batch_6a0504cd76388190b67c78250297573d |
completed | May 13, 2026, 11:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0505482c588190952fe07726f64b93 |
completed | May 13, 2026, 11:12 p.m. |
Created at: April 10, 2026, 11:44 a.m.