Triple

T495402
Position Surface form Disambiguated ID Type / Status
Subject European Russia E10281 entity
Predicate majorCity P316 FINISHED
Object Samara E67593 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: Samara | Statement: [European Russia, majorCity, Samara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Samara
Context triple: [European Russia, majorCity, Samara]
  • A. Samara chosen
    Samara is a major Russian city on the Volga River known as an important industrial, cultural, and transportation hub.
  • B. 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.
  • 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. Rostov-on-Don
    Rostov-on-Don is a major port city in southern Russia, located on the Don River near the Sea of Azov and serving as an important administrative, cultural, and industrial center of the region.
  • 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_69a2e847df8481909239ec08ccf1e376 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f0fdd5608190815fa36485df8962 completed Feb. 28, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a64a48e53081908e5d5e093edb5e75 completed March 3, 2026, 2:41 a.m.
Created at: Feb. 28, 2026, 1:12 p.m.