Triple

T9248784
Position Surface form Disambiguated ID Type / Status
Subject Yuri Bashmet E222264 entity
Predicate placeOfBirth P1 FINISHED
Object Rostov-on-Don E35707 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: Rostov-on-Don | Statement: [Yuri Bashmet, placeOfBirth, Rostov-on-Don]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rostov-on-Don
Context triple: [Yuri Bashmet, placeOfBirth, Rostov-on-Don]
  • A. Rostov-on-Don chosen
    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.
  • B. Rostov
    Rostov is one of Russia’s oldest and most historically significant towns, renowned for its well-preserved kremlin and traditional architecture.
  • C. Rostova
    Rostova is a Russian surname best known from Leo Tolstoy’s novel "War and Peace," where it is borne by members of the central Rostov family.
  • D. Volgograd
    Volgograd is a major city in southwestern Russia on the Volga River, historically known as Stalingrad and renowned as the site of one of World War II’s most pivotal and brutal battles.
  • E. Voronezh
    Voronezh is a major city in southwestern Russia, situated on the Voronezh River and serving as an important cultural, industrial, and transportation center.
  • 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_69ca841d2b18819089f9faf5b2c2aec0 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd05f6d62c8190a1e33f1854767b47 completed April 1, 2026, 11:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2572f5ccc81909f967dc69a8ae260 completed April 5, 2026, 12:35 p.m.
Created at: March 30, 2026, 7:31 p.m.