Triple

T9549343
Position Surface form Disambiguated ID Type / Status
Subject Karen Shakhnazarov E230378 entity
Predicate placeOfBirth P1 FINISHED
Object Krasnodar E175511 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: Krasnodar | Statement: [Karen Shakhnazarov, placeOfBirth, Krasnodar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Krasnodar
Context triple: [Karen Shakhnazarov, placeOfBirth, Krasnodar]
  • A. Krasnodar chosen
    Krasnodar is a major city in southern Russia, serving as the administrative center of Krasnodar Krai and an important economic and cultural hub of the region.
  • B. 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.
  • C. Stavropol
    Stavropol is a major administrative, cultural, and economic center in southwestern Russia, serving as the capital of Stavropol Krai in the North Caucasus region.
  • 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. Rostov
    Rostov is one of Russia’s oldest and most historically significant towns, renowned for its well-preserved kremlin and traditional architecture.
  • 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_69ca847d3be8819099c9dad2a7e786f1 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd99059138819088ae54b26df979cf completed April 1, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69d380c81c7c81908361d237d79f1ff0 completed April 6, 2026, 9:45 a.m.
Created at: March 30, 2026, 8:02 p.m.