Triple

T12077062
Position Surface form Disambiguated ID Type / Status
Subject Sokoloff E287577 entity
Predicate hasVariant P455 FINISHED
Object Sokolov E394625 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: Sokolov | Statement: [Sokoloff, hasVariant, Sokolov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sokolov
Context triple: [Sokoloff, hasVariant, Sokolov]
  • A. Sokolov chosen
    Sokolov is a town in the Karlovy Vary Region of the Czech Republic, known for its historical center and location in the Ohře River valley.
  • B. Gottwaldov
    Gottwaldov is the former name (1949–1990) of the Czech industrial city now known as Zlín, historically associated with the Baťa shoe company.
  • C. Mikulov
    Mikulov is a historic wine-producing town in the South Moravian region of the Czech Republic, known for its chateau, picturesque old town, and proximity to the Pálava Hills.
  • D. Zbyhněv
    Zbyhněv is a given name, likely a variant or regional form of the Slavic name Zbigniew.
  • E. Chomutov
    Chomutov is a city in the northwest of the Czech Republic known for its industrial heritage and location near the Ore Mountains.
  • 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_69d6ab4846e081908ee7bbd66a6d3459 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9045ceeec81909427cae8972eed26 completed April 10, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f660f48881908d50bf27b0892953 completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:48 p.m.