Triple

T13155245
Position Surface form Disambiguated ID Type / Status
Subject Kaluzhsko–Rizhskaya Line E312566 entity
Predicate hasStation P35 FINISHED
Object Tretyakovskaya E269783 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: Tretyakovskaya | Statement: [Kaluzhsko–Rizhskaya Line, hasStation, Tretyakovskaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tretyakovskaya
Context triple: [Kaluzhsko–Rizhskaya Line, hasStation, Tretyakovskaya]
  • A. Tretyakovskaya chosen
    Tretyakovskaya is a Moscow Metro station known for its central location and convenient transfers between multiple lines near the Tretyakov Gallery.
  • B. Smolny Embankment
    Smolny Embankment is a riverside promenade along the Neva in Saint Petersburg, Russia, known for its views of the Smolny Cathedral and surrounding historic architecture.
  • C. Tverskaya
    Tverskaya is a Moscow Metro station located in the city center, serving the busy Tverskaya Street area with access to major commercial and cultural sites.
  • D. Gorky Square
    Gorky Square is a central public square in Nizhny Novgorod, Russia, known as a major transport hub and urban gathering place.
  • E. Arbatskaya
    Arbatskaya is a Moscow Metro station located in the city center, known for its deep-level construction and ornate, grand architectural design.
  • 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c06ccb881909390df18e1a6f7ed completed April 10, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eaee8aa0819089994b85d56c7740 completed May 3, 2026, 6:27 a.m.
Created at: April 9, 2026, 9:12 p.m.