Triple
T18597362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aarhus Letbane |
E454525
|
entity |
| Predicate | hasDepot |
P2413
|
FINISHED |
| Object |
Banegraven depot
Banegraven depot is a maintenance and storage facility serving the Aarhus Letbane light rail system in Aarhus, Denmark.
|
E1333032
|
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: Banegraven depot | Statement: [Aarhus Letbane, hasDepot, Banegraven depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Banegraven depot Context triple: [Aarhus Letbane, hasDepot, Banegraven depot]
-
A.
Grunewald depot
Grunewald depot is a major maintenance and storage facility for Berlin’s U-Bahn trains, located in the Grunewald area of the city.
-
B.
Fürth depot
Fürth depot is a maintenance and storage facility serving the Nuremberg U-Bahn rapid transit system in the Fürth area of Germany.
-
C.
Nangang Depot
Nangang Depot is a major maintenance and storage facility serving Taipei's metro system in the Nangang District.
-
D.
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.
-
E.
Hyde Road depot
Hyde Road depot is a major bus operating and maintenance facility in Manchester used by Stagecoach Manchester for housing and servicing its fleet.
- 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: Banegraven depot Triple: [Aarhus Letbane, hasDepot, Banegraven depot]
Generated description
Banegraven depot is a maintenance and storage facility serving the Aarhus Letbane light rail system in Aarhus, Denmark.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Banegraven depot Target entity description: Banegraven depot is a maintenance and storage facility serving the Aarhus Letbane light rail system in Aarhus, Denmark.
-
A.
Grunewald depot
Grunewald depot is a major maintenance and storage facility for Berlin’s U-Bahn trains, located in the Grunewald area of the city.
-
B.
Fürth depot
Fürth depot is a maintenance and storage facility serving the Nuremberg U-Bahn rapid transit system in the Fürth area of Germany.
-
C.
Nangang Depot
Nangang Depot is a major maintenance and storage facility serving Taipei's metro system in the Nangang District.
-
D.
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.
-
E.
Hyde Road depot
Hyde Road depot is a major bus operating and maintenance facility in Manchester used by Stagecoach Manchester for housing and servicing its fleet.
- 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_69e5474ce0c08190b440cbe86b6ef7b9 |
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.