Triple

T5958784
Position Surface form Disambiguated ID Type / Status
Subject Zürich trolleybus network E132581 entity
Predicate hasDepot P2413 FINISHED
Object Hard depot
Hard depot is a major trolleybus facility in Zürich used for housing, maintaining, and dispatching vehicles on the city’s trolleybus network.
 E557739 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: Hard depot | Statement: [Zürich trolleybus network, hasDepot, Hard depot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hard depot
Context triple: [Zürich trolleybus network, hasDepot, Hard depot]
  • A. Nopo Depot
    Nopo Depot is a maintenance and storage facility serving the Busan Metro system in Busan, South Korea.
  • B. The Big Store
    The Big Store is a 1941 Marx Brothers comedy film featuring their trademark slapstick, wordplay, and musical numbers set in a chaotic department store.
  • C. 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.
  • D. The Shop
    The Shop is the historic Royal Military Academy in Woolwich, London, which served as the British Army’s principal training institution for artillery and engineering officers.
  • E. Vastral Depot
    Vastral Depot is a major maintenance and operations facility serving the Ahmedabad Metro system in Ahmedabad, India.
  • 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: Hard depot
Triple: [Zürich trolleybus network, hasDepot, Hard depot]
Generated description
Hard depot is a major trolleybus facility in Zürich used for housing, maintaining, and dispatching vehicles on the city’s trolleybus network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hard depot
Target entity description: Hard depot is a major trolleybus facility in Zürich used for housing, maintaining, and dispatching vehicles on the city’s trolleybus network.
  • A. Nopo Depot
    Nopo Depot is a maintenance and storage facility serving the Busan Metro system in Busan, South Korea.
  • B. The Big Store
    The Big Store is a 1941 Marx Brothers comedy film featuring their trademark slapstick, wordplay, and musical numbers set in a chaotic department store.
  • C. 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.
  • D. The Shop
    The Shop is the historic Royal Military Academy in Woolwich, London, which served as the British Army’s principal training institution for artillery and engineering officers.
  • E. Vastral Depot
    Vastral Depot is a major maintenance and operations facility serving the Ahmedabad Metro system in Ahmedabad, India.
  • 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.