Triple

T5958785
Position Surface form Disambiguated ID Type / Status
Subject Zürich trolleybus network E132581 entity
Predicate hasDepot P2413 FINISHED
Object Hagenholz depot
Hagenholz depot is a major maintenance and storage facility for trolleybuses serving the Zürich public transport network.
 E557740 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: Hagenholz depot | Statement: [Zürich trolleybus network, hasDepot, Hagenholz depot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hagenholz depot
Context triple: [Zürich trolleybus network, hasDepot, Hagenholz depot]
  • A. Elsau depot
    Elsau depot is a tram maintenance and storage facility serving the Strasbourg tramway network in Strasbourg, France.
  • B. Holtet depot
    Holtet depot is a tram depot in Oslo, Norway, serving as one of the main facilities for housing and maintaining the city's tram fleet.
  • C. Elfenau depot
    Elfenau depot is a tram facility in Bern, Switzerland, used for housing, maintaining, and dispatching vehicles on the Bern tram network.
  • D. 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.
  • E. Seestraße depot
    Seestraße depot is a major maintenance and storage facility for trains on Berlin’s U-Bahn rapid transit network.
  • 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: Hagenholz depot
Triple: [Zürich trolleybus network, hasDepot, Hagenholz depot]
Generated description
Hagenholz depot is a major maintenance and storage facility for trolleybuses serving the Zürich public transport network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hagenholz depot
Target entity description: Hagenholz depot is a major maintenance and storage facility for trolleybuses serving the Zürich public transport network.
  • A. Elsau depot
    Elsau depot is a tram maintenance and storage facility serving the Strasbourg tramway network in Strasbourg, France.
  • B. Holtet depot
    Holtet depot is a tram depot in Oslo, Norway, serving as one of the main facilities for housing and maintaining the city's tram fleet.
  • C. Elfenau depot
    Elfenau depot is a tram facility in Bern, Switzerland, used for housing, maintaining, and dispatching vehicles on the Bern tram network.
  • D. 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.
  • E. Seestraße depot
    Seestraße depot is a major maintenance and storage facility for trains on Berlin’s U-Bahn rapid transit network.
  • 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_69c0086c2364819091e9fe2f58fa2517 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c039c48d0c81908e794c52fddf2ca2 completed March 22, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e3e3736c8190b445156f0c1bdf1f completed March 23, 2026, 6:55 a.m.
NEDg Description generation batch_69c0ec751abc8190a1f6d09e8c47cd59 completed March 23, 2026, 7:32 a.m.
NED2 Entity disambiguation (via description) batch_69c0ed1871a88190a2894e7e156478d7 completed March 23, 2026, 7:34 a.m.
Created at: March 22, 2026, 4:02 p.m.