Triple

T18576272
Position Surface form Disambiguated ID Type / Status
Subject Ales Bialiatski E453995 entity
Predicate placeOfBirth P1 FINISHED
Object Vyartsilya NE NERFINISHED

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: Vyartsilya | Statement: [Ales Bialiatski, placeOfBirth, Vyartsilya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vyartsilya
Context triple: [Ales Bialiatski, placeOfBirth, Vyartsilya]
  • A. Vyartsilya chosen
    Vyartsilya is a small urban-type settlement in the Republic of Karelia, Russia, near the border with Finland.
  • B. Bykovsky
    Bykovsky is a rural locality (selo) in the Bulunsky District of the Sakha Republic, Russia, situated in the Arctic region along the Lena River.
  • C. Komarova
    Komarova is the feminine form of the Russian surname Komarov, commonly borne by women in Russian-speaking countries.
  • D. Kozhedub
    Kozhedub is a Slavic surname most famously borne by Ivan Kozhedub, a highly decorated Soviet World War II fighter ace.
  • E. Venora
    Venora is the surname of American actress Diane Venora, known for her work in film, television, and theater.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38974308190a9174430ef256b73 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e543c9d26c8190a80dda411cd0c9ac completed April 19, 2026, 9:06 p.m.
Created at: April 10, 2026, 11:43 a.m.