Triple

T8279754
Position Surface form Disambiguated ID Type / Status
Subject Ante Razov E193639 entity
Predicate hasSurname P18 FINISHED
Object Razov E193639 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: Razov | Statement: [Ante Razov, hasSurname, Razov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Razov
Context triple: [Ante Razov, hasSurname, Razov]
  • A. Razov chosen
    Razov is a surname most notably associated with Ante Razov, a former American professional soccer player and prolific Major League Soccer goal scorer.
  • B. Razlog
    Razlog is a small Bulgarian town nestled in a mountain valley near the popular ski resort of Bansko, known for its scenic surroundings and traditional architecture.
  • C. Ruz
    Ruz is a Spanish-language surname most notably associated with the family of Cuban leader Fidel Castro through his mother, Lina Ruz González.
  • D. Rzav
    Rzav is a river in the western Balkans that flows through Serbia and Bosnia and Herzegovina before joining the Drina River.
  • E. Raka
    Raka is a renowned Afrikaans narrative poem by N. P. van Wyk Louw that explores themes of civilization, barbarism, and moral conflict through an allegorical tale.
  • 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_69ca82e217a48190880695635c44b2ed completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb79ece5708190a1569bcfad5b3644 completed March 31, 2026, 7:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd686d9be081908b0490e708f51ad7 completed April 1, 2026, 6:48 p.m.
Created at: March 30, 2026, 5:51 p.m.