Triple

T5840706
Position Surface form Disambiguated ID Type / Status
Subject Trikken i Oslo E129584 entity
Predicate hasDepot P2413 FINISHED
Object 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.
 E551927 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: Grefsen tram depot | Statement: [Trikken i Oslo, hasDepot, Grefsen tram depot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Grefsen tram depot
Context triple: [Trikken i Oslo, hasDepot, Grefsen tram depot]
  • A. Hammarby depot
    Hammarby depot is a maintenance and storage facility serving Stockholm’s Tvärbanan light rail system.
  • B. 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.
  • C. Seestraße depot
    Seestraße depot is a major maintenance and storage facility for trains on Berlin’s U-Bahn rapid transit network.
  • D. Steintor tram stop
    Steintor tram stop is a public tram station in Hanover, Germany, serving as a key transit point near the Gehry Tower and the city center.
  • E. Fürth depot
    Fürth depot is a maintenance and storage facility serving the Nuremberg U-Bahn rapid transit system in the Fürth area of Germany.
  • 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: Grefsen tram depot
Triple: [Trikken i Oslo, hasDepot, Grefsen tram depot]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Grefsen tram depot
Target entity description: 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.
  • A. Hammarby depot
    Hammarby depot is a maintenance and storage facility serving Stockholm’s Tvärbanan light rail system.
  • B. 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.
  • C. Seestraße depot
    Seestraße depot is a major maintenance and storage facility for trains on Berlin’s U-Bahn rapid transit network.
  • D. Steintor tram stop
    Steintor tram stop is a public tram station in Hanover, Germany, serving as a key transit point near the Gehry Tower and the city center.
  • E. Fürth depot
    Fürth depot is a maintenance and storage facility serving the Nuremberg U-Bahn rapid transit system in the Fürth area of Germany.
  • 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_69c0084bd31c8190a796bb6284845e83 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c034d6f09c81908dfb3c2c51a2f5a9 completed March 22, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a19e4ec4819099fa5c6fe9a6a257 completed March 23, 2026, 2:12 a.m.
NEDg Description generation batch_69c0a572f52481908fc4f2a833fd8edf completed March 23, 2026, 2:29 a.m.
NED2 Entity disambiguation (via description) batch_69c0a5d17d5c8190a5fe816d29400894 completed March 23, 2026, 2:30 a.m.
Created at: March 22, 2026, 3:54 p.m.