Triple

T436040
Position Surface form Disambiguated ID Type / Status
Subject Russia E10011 entity
Predicate hasMajorCity P316 FINISHED
Object Kazan E35521 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: Kazan | Statement: [Russia, hasMajorCity, Kazan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kazan
Context triple: [Russia, hasMajorCity, Kazan]
  • A. Kazan chosen
    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.
  • B. Samara
    Samara is a major Russian city on the Volga River known as an important industrial, cultural, and transportation hub.
  • C. 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.
  • D. Grozny
    Grozny is the capital and largest city of the Chechen Republic in southwestern Russia, known for its turbulent recent history and extensive post-war reconstruction.
  • E. Saratov
    Saratov is a major city in southwestern Russia known as an important cultural, educational, and industrial center on the banks of the Volga River.
  • 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_69a2e8465ef481909655c681b01e2986 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2ef0c97188190b62104cb639d4b60 completed Feb. 28, 2026, 1:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69a52383450081908b945646a3e231c2 completed March 2, 2026, 5:43 a.m.
Created at: Feb. 28, 2026, 1:11 p.m.