Triple

T9313934
Position Surface form Disambiguated ID Type / Status
Subject Minsk Metro E224070 entity
Predicate hasDepot P2413 FINISHED
Object Mogilevskoe depot
Mogilevskoe depot is a maintenance and storage facility serving the rolling stock of the Minsk Metro system in Belarus.
E793637 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: Mogilevskoe depot | Statement: [Minsk Metro, hasDepot, Mogilevskoe depot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mogilevskoe depot
Context triple: [Minsk Metro, hasDepot, Mogilevskoe depot]
  • A. Moskovskoe depot
    Moskovskoe depot is a maintenance and storage facility serving the Minsk Metro system in Minsk, Belarus.
  • B. Kholodna Hora depot
    Kholodna Hora depot is a maintenance and storage facility serving the Kharkiv Metro system in Kharkiv, Ukraine.
  • C. Vykhino depot
    Vykhino depot is a maintenance and storage facility serving trains of the Tagansko–Krasnopresnenskaya Line of the Moscow Metro.
  • D. Traktorozavodskaya station
    Traktorozavodskaya station is a stop on Volgograd’s Metrotram system serving the industrial Traktorozavodsky district of the city.
  • E. Zavod Krasny Oktyabr station
    Zavod Krasny Oktyabr station is a tram-station stop on the Volgograd Metrotram system serving the industrial area around the historic Krasny Oktyabr (Red October) factory in Volgograd, Russia.
  • 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: Mogilevskoe depot
Triple: [Minsk Metro, hasDepot, Mogilevskoe depot]
Generated description
Mogilevskoe depot is a maintenance and storage facility serving the rolling stock of the Minsk Metro system in Belarus.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mogilevskoe depot
Target entity description: Mogilevskoe depot is a maintenance and storage facility serving the rolling stock of the Minsk Metro system in Belarus.
  • A. Moskovskoe depot
    Moskovskoe depot is a maintenance and storage facility serving the Minsk Metro system in Minsk, Belarus.
  • B. Kholodna Hora depot
    Kholodna Hora depot is a maintenance and storage facility serving the Kharkiv Metro system in Kharkiv, Ukraine.
  • C. Vykhino depot
    Vykhino depot is a maintenance and storage facility serving trains of the Tagansko–Krasnopresnenskaya Line of the Moscow Metro.
  • D. Traktorozavodskaya station
    Traktorozavodskaya station is a stop on Volgograd’s Metrotram system serving the industrial Traktorozavodsky district of the city.
  • E. Zavod Krasny Oktyabr station
    Zavod Krasny Oktyabr station is a tram-station stop on the Volgograd Metrotram system serving the industrial area around the historic Krasny Oktyabr (Red October) factory in Volgograd, Russia.
  • 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_69ca8425f4fc81909c1c586e9a5b7530 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd20b048a081909fd7ec0b6b863063 completed April 1, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0e39d03508190aca18600c33bfdd8 completed April 4, 2026, 10:10 a.m.
NEDg Description generation batch_69d0e57272cc819085a1fd3e356d7c46 completed April 4, 2026, 10:18 a.m.
NED2 Entity disambiguation (via description) batch_69d0e72c3d088190953a5929f8b861d8 completed April 4, 2026, 10:25 a.m.
Created at: March 30, 2026, 7:37 p.m.