Triple

T23380388
Position Surface form Disambiguated ID Type / Status
Subject Ontario gaming market E593727 entity
Predicate lotteryBrand P152511 FINISHED
Object OLG — NE NERFINISHED

How this triple was built (4 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: OLG | Statement: [Ontario gaming market, lotteryBrand, OLG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: OLG
Context triple: [Ontario gaming market, lotteryBrand, OLG]
  • A. OLY
    OLY is the commonly used abbreviation for Olympiacos FC, a major Greek football club based in Piraeus.
  • B. Sazka
    Sazka is a Czech lottery and betting company that has also been a prominent sponsor of major sports and entertainment venues.
  • C. 6 OG
    6 OG is the abbreviated designation for the 6th Operations Group, a U.S. Air Force unit responsible for aerial refueling and related operational missions.
  • D. OLA
    OLA is the commonly used acronym for the United Nations Office of Legal Affairs, which provides legal advice and support to UN organs and specialized agencies.
  • E. OLA
    OLA is a laser altimeter instrument on NASA’s OSIRIS-REx spacecraft used to create detailed 3D maps of the asteroid Bennu’s surface.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: OLG
Target entity description: OLG is the Ontario Lottery and Gaming Corporation, the government agency responsible for operating lotteries, casinos, and other regulated gaming activities in Ontario, Canada.
  • A. OLY
    OLY is the commonly used abbreviation for Olympiacos FC, a major Greek football club based in Piraeus.
  • B. Sazka
    Sazka is a Czech lottery and betting company that has also been a prominent sponsor of major sports and entertainment venues.
  • C. 6 OG
    6 OG is the abbreviated designation for the 6th Operations Group, a U.S. Air Force unit responsible for aerial refueling and related operational missions.
  • D. OLA
    OLA is the commonly used acronym for the United Nations Office of Legal Affairs, which provides legal advice and support to UN organs and specialized agencies.
  • E. OLA
    OLA is a laser altimeter instrument on NASA’s OSIRIS-REx spacecraft used to create detailed 3D maps of the asteroid Bennu’s surface.
  • F. None of above. chosen
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: lotteryBrand
Context triple: [Ontario gaming market, lotteryBrand, OLG]
  • A. lotteryNumbersSource
    Indicates the origin or provider from which the lottery numbers are obtained or generated.
  • B. GoldenBallWinner
    Indicates that the subject has been awarded the Golden Ball, recognizing them as the best-performing player in a particular football (soccer) tournament or competition.
  • C. MagicWins
    Indicates that one entity achieves victory over another through the use of magic or supernatural powers.
  • D. LuckySevenPredecessorGame
    Indicates a game-related relationship where one entity is the immediate predecessor of another in a sequence or state transition specifically associated with a "lucky seven" condition or rule.
  • E. franchiseBrand
    Indicates that one entity is the brand under which another entity operates as a franchise.
  • F. None of above. chosen

Provenance (4 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_69e25d268a50819095f2fd479da8ef3f completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1a3b6ddfc8190a23d291286f3fe42 completed April 29, 2026, 6:22 a.m.
PD Predicate disambiguation batch_69f061c7aaa48190a58ce93f87155ffc completed April 28, 2026, 7:29 a.m.
PDg Predicate description generation batch_69f0bd4a0e408190ad8916faf23562d9 completed April 28, 2026, 1:59 p.m.
Created at: April 17, 2026, 5:34 p.m.