Triple

T8848098
Position Surface form Disambiguated ID Type / Status
Subject Moscow Railway E210559 entity
Predicate connectsTo P845 FINISHED
Object Gorky Railway E707607 NE FINISHED

How this triple was built (2 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: Gorky Railway | Statement: [Moscow Railway, connectsTo, Gorky Railway]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gorky Railway
Context triple: [Moscow Railway, connectsTo, Gorky Railway]
  • A. Gorky Railway chosen
    Gorky Railway is a major regional railway network in Russia that operates routes across the Volga-Vyatka area, including services through Kazan.
  • B. Repin train
    The Repin train was a former international passenger rail service that connected Saint Petersburg and Helsinki before being superseded by the high-speed Allegro trains.
  • C. Stalinets
    Stalinets was the former name of the Russian football club now known as Lokomotiv Moscow.
  • D. Zheleznodorozhny
    Zheleznodorozhny is a small Russian settlement located in Siberia, known for its position along the Kirenga River and its origins as a railway-related community.
  • E. Red Star
    Red Star is a major Serbian professional football club based in Belgrade, renowned for its passionate fan base and success in domestic and European competitions, including winning the 1991 European Cup.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca838967bc8190b46c3c80a2887ea4 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc60aa6db0819097c3257499200afc completed April 1, 2026, 12:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf89bd3ef48190a6a2efff18db4dbd completed April 3, 2026, 9:34 a.m.
Created at: March 30, 2026, 6:49 p.m.