Triple

T13719828
Position Surface form Disambiguated ID Type / Status
Subject Nizhegorodskaya MCC station E328999 entity
Predicate ownedBy P347 FINISHED
Object City of Moscow E1747 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: City of Moscow | Statement: [Nizhegorodskaya MCC station, ownedBy, City of Moscow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Moscow
Context triple: [Nizhegorodskaya MCC station, ownedBy, City of Moscow]
  • A. Moscow City
    Moscow City is a modern high-rise business district in western Moscow known for its cluster of skyscrapers, financial institutions, and commercial developments.
  • B. Mosca
    Mosca is the cunning and manipulative servant in Ben Jonson’s play "Volpone," known for orchestrating deceptions and driving much of the plot’s dark comedy.
  • C. Pushkino
    Pushkino is a town in Russia that serves as a suburban residential and industrial center northeast of Moscow.
  • D. Moscow
    Moscow is a small borough in Lackawanna County, Pennsylvania, known as a residential community near the Scranton metropolitan area.
  • E. Moscow chosen
    Moscow is the capital and largest city of Russia, serving as its political, economic, and cultural center.
  • 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_69d80770b9bc81909f70c8c317d53cff completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dd439a121c81908cae964e7756274c completed April 13, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69f79d5c4f848190993f829824eabbef completed May 3, 2026, 7:09 p.m.
Created at: April 9, 2026, 9:55 p.m.