Triple

T382756
Position Surface form Disambiguated ID Type / Status
Subject Russian Provisional Government E8715 entity
Predicate capital P234 FINISHED
Object Petrograd E38138 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: [Russian Provisional Government, capital, Petrograd]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Petrograd
Context triple: [Russian Provisional Government, capital, Petrograd]
  • A. Moscow
    Moscow is the capital and largest city of Russia, serving as its political, economic, and cultural center.
  • B. Tsaritsyn
    Tsaritsyn was the original name of the Russian city now known as Volgograd, a major industrial and historical center on the Volga River.
  • C. Kazan
    Kazan is a major city in western Russia and the capital of the Republic of Tatarstan, known for its rich Tatar-Russian cultural heritage and historic Kremlin.
  • D. Yekaterinburg
    Yekaterinburg is a major industrial and cultural city in Russia’s Ural region, historically known as the site of the execution of the last Russian tsar, Nicholas II, and his family.
  • E. Tsentralny District of Saint Petersburg chosen
    Tsentralny District of Saint Petersburg is the historic and administrative heart of the city, encompassing its main cultural, governmental, and commercial centers.
  • 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_69a2e7f47dd08190a4e294ccbbe46cd4 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec40ff8c81909306eb2dfe1512af completed Feb. 28, 2026, 1:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4a424e0d88190b0ad5d0827b762ae completed March 1, 2026, 8:40 p.m.
Created at: Feb. 28, 2026, 1:08 p.m.