Triple

T15300200
Position Surface form Disambiguated ID Type / Status
Subject Novosibirsk Metro E365764 entity
Predicate hasStation P35 FINISHED
Object Oktyabrskaya E229950 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: Oktyabrskaya | Statement: [Novosibirsk Metro, hasStation, Oktyabrskaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oktyabrskaya
Context triple: [Novosibirsk Metro, hasStation, Oktyabrskaya]
  • A. Oktyabrskaya chosen
    Oktyabrskaya is a Moscow Metro station known for its distinctive Soviet-era architecture and role as a key transfer point in the city’s subway network.
  • B. Oktyabrsk
    Oktyabrsk is a small industrial city in Russia located on the Volga River within Samara Oblast.
  • C. Oktyabrsky
    Oktyabrsky is a Russian surname most notably borne by Soviet Admiral Filipp Oktyabrsky, a prominent naval commander during World War II.
  • D. Oktyabrsky
    Oktyabrsky is a significant industrial city in the Republic of Bashkortostan, Russia, known for its oil and gas industry.
  • E. Black October (Russia)
    Black October (Russia) refers to the violent climax of the 1993 Russian constitutional crisis, when a power struggle between President Boris Yeltsin and the parliament led to armed clashes and the shelling of the Russian White House in Moscow.
  • 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0368869f8819098cf9e7801e37548 completed April 16, 2026, 1:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69feef8513a08190b2d2a7dde85dd43d completed May 9, 2026, 8:25 a.m.
Created at: April 10, 2026, 3:15 a.m.