Triple

T3305894
Position Surface form Disambiguated ID Type / Status
Subject Lavr Kornilov E69447 entity
Predicate placeOfActivity P1527 FINISHED
Object Petrograd E90774 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: Petrograd | Statement: [Lavr Kornilov, placeOfActivity, Petrograd]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Petrograd
Context triple: [Lavr Kornilov, placeOfActivity, Petrograd]
  • A. Pushkino
    Pushkino is a town in Russia that serves as a suburban residential and industrial center northeast of Moscow.
  • B. Leningrad chosen
    Leningrad, now known as Saint Petersburg, is a major Russian city on the Baltic Sea that served as the imperial capital and endured a devastating World War II siege.
  • C. Moscow
    Moscow is the capital and largest city of Russia, serving as its political, economic, and cultural center.
  • D. 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.
  • E. Sofya
    Sofya is the Russian given name of Sophia Tolstaya, the wife and muse of novelist Leo Tolstoy.
  • 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_69ad859f218081909458d2cebbf57565 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb0c9470881908c36c1984fdbb67b completed March 8, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3341e2f508190a21411869375e3e1 completed March 12, 2026, 9:46 p.m.
Created at: March 8, 2026, 3:11 p.m.