Triple

T14098155
Position Surface form Disambiguated ID Type / Status
Subject Sokolovskaya E339308 entity
Predicate hasTransliteration P2508 FINISHED
Object Sokolovska E969365 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: Sokolovska | Statement: [Sokolovskaya, hasTransliteration, Sokolovska]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sokolovska
Context triple: [Sokolovskaya, hasTransliteration, Sokolovska]
  • A. Sokolova chosen
    Sokolova is a common Slavic feminine surname, especially prevalent in Russian-speaking countries.
  • B. Pekarová
    Pekarová is a Czech or Slovak feminine surname derived from the masculine form Pekar.
  • C. Zátopková
    Zátopková is the surname of Dana Zátopková, a renowned Czech javelin thrower and Olympic champion.
  • D. Černová
    Černová is a village in northern Slovakia, historically known as the birthplace of Slovak nationalist priest and politician Andrej Hlinka.
  • E. Kotešová
    Kotešová is a village and municipality in northern Slovakia, situated in the Žilina Region.
  • 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_69d81c69b5c8819094aa1abf18302908 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5fb926288190a7f0f50d1d585d76 completed April 14, 2026, 3:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd0adfc28819097a1bfd56739c286 completed May 7, 2026, 5:49 p.m.
Created at: April 9, 2026, 10:22 p.m.