Triple

T22001664
Position Surface form Disambiguated ID Type / Status
Subject Casey Silver E543339 entity
Predicate notableWork P4 FINISHED
Object Casino 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: Casino | Statement: [Casey Silver, notableWork, Casino]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Casino
Context triple: [Casey Silver, notableWork, Casino]
  • A. Casino chosen
    "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.
  • B. 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.
  • C. Casino
    "Casino" is a 1978 jazz fusion album by guitarist Al Di Meola, showcasing his virtuosic playing and intricate Latin-influenced compositions.
  • D. Casino 2000
    Casino 2000 is a prominent entertainment complex in Mondorf-les-Bains, Luxembourg, featuring a casino, dining venues, and event spaces.
  • E. Bringing Down the House
    Bringing Down the House is a bestselling non-fiction book by Ben Mezrich that chronicles how a team of MIT students used card-counting techniques to win millions of dollars in Las Vegas blackjack casinos.
  • 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_69e11e2c814c8190837d072789000486 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1276ae4e0819097bf1b978451f776 completed April 28, 2026, 9:32 p.m.
Created at: April 16, 2026, 8:20 p.m.