Triple

T22395520
Position Surface form Disambiguated ID Type / Status
Subject Ouija E553618 entity
Predicate musicBy P1952 FINISHED
Object Anton Sanko 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: Anton Sanko | Statement: [Ouija, musicBy, Anton Sanko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anton Sanko
Context triple: [Ouija, musicBy, Anton Sanko]
  • A. Anton Sanko chosen
    Anton Sanko is an American composer and producer known for his film and television scores, particularly in the horror and thriller genres.
  • B. Anton Romako
    Anton Romako was a 19th-century Austrian painter known for his psychologically intense portraits and innovative, expressive style that anticipated aspects of modern art.
  • C. Andrei Sator
    Andrei Sator is the main antagonist in Christopher Nolan's film "Tenet," a powerful Russian oligarch who orchestrates a time-inverting global catastrophe.
  • D. Anton Valter
    Anton Valter was a physicist associated with the Kharkiv Institute of Physics and Technology, known for his contributions to Soviet-era scientific research.
  • E. Anton Zafir
    Anton Zafir is a mixed martial artist who has competed in the UFC’s welterweight division.
  • 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_69e11e4cf87c8190a1ff474daec326b7 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1585e84b081908c95ed3e0d987ed8 completed April 29, 2026, 1:01 a.m.
Created at: April 16, 2026, 8:45 p.m.