Triple

T1011613
Position Surface form Disambiguated ID Type / Status
Subject Leningrad, Russian SFSR, Soviet Union E21835 entity
Predicate formerNameOf P65 FINISHED
Object Saint Petersburg E916 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: Saint Petersburg | Statement: [Leningrad, Russian SFSR, Soviet Union, formerNameOf, Saint Petersburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saint Petersburg
Context triple: [Leningrad, Russian SFSR, Soviet Union, formerNameOf, Saint Petersburg]
  • A. St. Petersburg chosen
    St. Petersburg is a major Russian port city on the Baltic Sea, renowned for its imperial architecture, cultural heritage, and role as a historic capital of Russia.
  • B. Novgorod
    Novgorod is one of the oldest and historically most important cities of Russia, a major medieval political and cultural center that played a key role in the formation of the early Russian state.
  • C. Arkhangelsk
    Arkhangelsk is a historic port city in northern Russia on the White Sea, long serving as a key maritime gateway and administrative center of the surrounding region.
  • D. Pushkino
    Pushkino is a town in Russia that serves as a suburban residential and industrial center northeast of Moscow.
  • E. Moscow
    Moscow is a fictional character from the Spanish television series "Money Heist" (La Casa de Papel), known as a kind-hearted, blue-collar miner and the father of Denver who participates in the Royal Mint heist.
  • 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_69a493c68e24819080ed0ee8bcfd5ce0 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b7a743cc8190a46e6a14e3e8130f completed March 1, 2026, 10:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac7f29385c8190a42dc7dbac592221 completed March 7, 2026, 7:40 p.m.
Created at: March 1, 2026, 7:41 p.m.