Triple

T10526603
Position Surface form Disambiguated ID Type / Status
Subject Sully Boyar E248321 entity
Predicate notableWork P4 FINISHED
Object The Gambler E660520 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: The Gambler | Statement: [Sully Boyar, notableWork, The Gambler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Gambler
Context triple: [Sully Boyar, notableWork, The Gambler]
  • A. The Gambler
    The Gambler is a classic country song and album by Kenny Rogers that tells the story of life lessons learned from a seasoned card player, becoming one of his signature hits.
  • B. The Gambler chosen
    The Gambler is a 1974 American drama film starring James Caan as a literature professor whose secret gambling addiction spirals out of control.
  • C. The Gambler
    The Gambler is a short novel by Fyodor Dostoevsky that explores obsession, addiction, and psychological turmoil through the story of a tutor ensnared by roulette and destructive love.
  • D. Casino
    "Casino" is a 1995 crime drama film directed by Martin Scorsese that explores the rise and fall of a Las Vegas casino boss and the mob's influence over the gambling industry.
  • E. Casino
    Casino is a town in northern New South Wales, Australia, known as a regional service centre and gateway to the surrounding agricultural and beef-producing areas.
  • 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_69d381c5c7448190bec34bee7ec72bac completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509f4bbe88190bce7789a56c85671 completed April 7, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69d90e26c4908190b77d73c11bee6119 completed April 10, 2026, 2:50 p.m.
Created at: April 6, 2026, 12:29 p.m.