Triple
T4548926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bern tram network |
E110113
|
entity |
| Predicate | hasDepot |
P2413
|
FINISHED |
| Object |
Bümpliz depot
Bümpliz depot is a tram facility in the Bümpliz district of Bern used for housing, maintaining, and dispatching vehicles of the city’s tram network.
|
E452072
|
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: Bümpliz depot | Statement: [Bern tram network, hasDepot, Bümpliz depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bümpliz depot Context triple: [Bern tram network, hasDepot, Bümpliz depot]
-
A.
Vastral Depot
Vastral Depot is a major maintenance and operations facility serving the Ahmedabad Metro system in Ahmedabad, India.
-
B.
Gogar depot
Gogar depot is the main maintenance and operations facility for the Edinburgh Trams light rail system in Edinburgh, Scotland.
-
C.
Fürth depot
Fürth depot is a maintenance and storage facility serving the Nuremberg U-Bahn rapid transit system in the Fürth area of Germany.
-
D.
Carnide depot
Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
-
E.
Planernoye depot
Planernoye depot is a maintenance and storage facility serving trains on Moscow’s Tagansko–Krasnopresnenskaya metro 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: Bümpliz depot Triple: [Bern tram network, hasDepot, Bümpliz depot]
Generated description
Bümpliz depot is a tram facility in the Bümpliz district of Bern used for housing, maintaining, and dispatching vehicles of the city’s tram network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bümpliz depot Target entity description: Bümpliz depot is a tram facility in the Bümpliz district of Bern used for housing, maintaining, and dispatching vehicles of the city’s tram network.
-
A.
Vastral Depot
Vastral Depot is a major maintenance and operations facility serving the Ahmedabad Metro system in Ahmedabad, India.
-
B.
Gogar depot
Gogar depot is the main maintenance and operations facility for the Edinburgh Trams light rail system in Edinburgh, Scotland.
-
C.
Fürth depot
Fürth depot is a maintenance and storage facility serving the Nuremberg U-Bahn rapid transit system in the Fürth area of Germany.
-
D.
Carnide depot
Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
-
E.
Planernoye depot
Planernoye depot is a maintenance and storage facility serving trains on Moscow’s Tagansko–Krasnopresnenskaya metro 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_69bd4412524c8190be5bcc9ddee91848 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57f272248190983ae439bd0ac0cc |
completed | March 20, 2026, 2:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdb945bd3881908e6c3f5f91b5f38e |
completed | March 20, 2026, 9:16 p.m. |
| NEDg | Description generation | batch_69bdbecf94d0819087519e44aab5a035 |
completed | March 20, 2026, 9:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bdbf81f1208190946611fb6a1c20ba |
completed | March 20, 2026, 9:43 p.m. |
Created at: March 20, 2026, 1:05 p.m.