Triple

T20174972
Position Surface form Disambiguated ID Type / Status
Subject Binion's Gambling Hall and Hotel E492065 entity
Predicate namedAfter P63 FINISHED
Object Benny Binion 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: Benny Binion | Statement: [Binion's Gambling Hall and Hotel, namedAfter, Benny Binion]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Benny Binion
Context triple: [Binion's Gambling Hall and Hotel, namedAfter, Benny Binion]
  • A. Benny Binion chosen
    Benny Binion was an American casino owner and gambling icon who transformed Las Vegas poker by creating the World Series of Poker and popularizing high-stakes tournament play.
  • B. William F. Harrah
    William F. Harrah was an American casino owner and gambling industry pioneer best known for founding Harrah’s Hotels and Casinos in Nevada.
  • C. Kalita Humphreys
    Kalita Humphreys was an American actress in whose honor the Kalita Humphreys Theater in Dallas, Texas, was named.
  • D. Bobby Joe Hooper
    Bobby Joe Hooper is a notable alumnus of Cartersville High School recognized for his achievements after graduating from the institution.
  • E. William Nack
    William Nack was an American sportswriter and author best known for his definitive biography of the racehorse Secretariat.
  • 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_69da6266c6888190bc1a3ecf24814d34 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e668eaa3b88190bef4f2db0125fdfc completed April 20, 2026, 5:56 p.m.
Created at: April 11, 2026, 11:36 p.m.