Triple

T12213613
Position Surface form Disambiguated ID Type / Status
Subject Rybinsk E291027 entity
Predicate hasRailwayConnectionTo P3791 FINISHED
Object Danilov E761661 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: Danilov | Statement: [Rybinsk, hasRailwayConnectionTo, Danilov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danilov
Context triple: [Rybinsk, hasRailwayConnectionTo, Danilov]
  • A. Danilov chosen
    Danilov is a Russian masculine surname, from which the feminine form Danilova is derived.
  • B. Piotrovsky
    Piotrovsky is a Russian surname most prominently associated with Mikhail Piotrovsky, the long-serving director of the State Hermitage Museum in Saint Petersburg.
  • C. Kaluzhskaya
    Kaluzhskaya is a Moscow Metro station on the Kaluzhsko–Rizhskaya line, serving the southwestern part of the city.
  • D. Gorkovskaya
    Gorkovskaya was the former name of Moscow’s central Tverskaya metro station, reflecting its Soviet-era designation.
  • E. Kolomenskaya
    Kolomenskaya is a Moscow Metro station on the Zamoskvoretskaya Line, serving the Kolomenskoye area in the southern part of the city.
  • 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_69d6ab65923081909acfc61b7a612233 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91c931cec819083ca19be06a33e1c completed April 10, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60aa13f64819096dc23295a6f0cdb completed May 2, 2026, 2:30 p.m.
Created at: April 8, 2026, 9:51 p.m.