Triple

T19587383
Position Surface form Disambiguated ID Type / Status
Subject Yerevan Metro E470137 entity
Predicate hasDepot P2413 FINISHED
Object Shengavit depot NE NERFINISHED

How this triple was built (3 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: Shengavit depot | Statement: [Yerevan Metro, hasDepot, Shengavit depot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shengavit depot
Context triple: [Yerevan Metro, hasDepot, Shengavit depot]
  • A. Suseo Depot
    Suseo Depot is a maintenance and storage facility serving trains operating on Seoul Subway Line 3 in South Korea.
  • B. Carnide depot
    Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
  • 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. Vastral Depot
    Vastral Depot is a major maintenance and operations facility serving the Ahmedabad Metro system in Ahmedabad, India.
  • E. 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.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Shengavit depot
Target entity description: Shengavit depot is the main maintenance and storage facility serving the Yerevan Metro system in Armenia’s capital.
  • A. Suseo Depot
    Suseo Depot is a maintenance and storage facility serving trains operating on Seoul Subway Line 3 in South Korea.
  • B. Carnide depot
    Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
  • 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. Vastral Depot
    Vastral Depot is a major maintenance and operations facility serving the Ahmedabad Metro system in Ahmedabad, India.
  • E. 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.
  • F. None of above. chosen

Provenance (2 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_69d8e510024481908415c0d616fa6186 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e64052f61c81908bb49927d4246030 completed April 20, 2026, 3:03 p.m.
Created at: April 10, 2026, 1:43 p.m.