Triple

T18204696
Position Surface form Disambiguated ID Type / Status
Subject OPT E435873 entity
Predicate largestModel P4495 FINISHED
Object OPT-175B 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: OPT-175B | Statement: [OPT, largestModel, OPT-175B]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OPT-175B
Context triple: [OPT, largestModel, OPT-175B]
  • A. Opti
    Opti is a friendly, futuristic robot character that served as one of the official mascots of Expo 2020 Dubai.
  • B. OK-150
    OK-150 is a Soviet-era marine nuclear reactor design used to power early nuclear icebreakers such as the Lenin.
  • C. BPS-17
    BPS-17 is a mid-level government job grade in Pakistan’s Basic Pay Scale system, typically associated with entry-level positions for officers and professionals such as civil servants, engineers, and lecturers.
  • D. B17
    B17 is a New York City bus route that operates in Brooklyn, connecting the Canarsie neighborhood with other parts of the borough.
  • E. H175
    The H175 is a medium-lift, twin-engine helicopter developed by Airbus Helicopters, widely used for offshore transport, search and rescue, and other civil missions.
  • 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: OPT-175B
Target entity description: OPT-175B is Meta AI’s largest OPT-series language model, featuring 175 billion parameters for advanced natural language understanding and generation.
  • A. Opti
    Opti is a friendly, futuristic robot character that served as one of the official mascots of Expo 2020 Dubai.
  • B. OK-150
    OK-150 is a Soviet-era marine nuclear reactor design used to power early nuclear icebreakers such as the Lenin.
  • C. BPS-17
    BPS-17 is a mid-level government job grade in Pakistan’s Basic Pay Scale system, typically associated with entry-level positions for officers and professionals such as civil servants, engineers, and lecturers.
  • D. B17
    B17 is a New York City bus route that operates in Brooklyn, connecting the Canarsie neighborhood with other parts of the borough.
  • E. H175
    The H175 is a medium-lift, twin-engine helicopter developed by Airbus Helicopters, widely used for offshore transport, search and rescue, and other civil missions.
  • F. None of above. chosen
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: largestModel
Context triple: [OPT, largestModel, OPT-175B]
  • A. modelSize
    Indicates the quantitative measure of how large or complex a model is, typically in terms of parameters, layers, or memory footprint.
  • B. isLargestOf chosen
    Indicates that one entity has the greatest size, extent, or magnitude among a specified set of entities.
  • C. createdOneOfLargest
    Indicates that an entity is responsible for creating something that ranks among the largest within a given group or category.
  • D. largestFigureLengthApprox
    Indicates an approximate measurement of the length of the largest figure involved in the relationship or context.
  • E. largestOperator
    Indicates that the subject is the operator with the greatest size, capacity, or scale among a specified set of operators.
  • F. None of above.

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_69d8b90dba6481908e119eb9aa4ca0cb completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4e222831081908f7d5500424e3acb completed April 19, 2026, 2:09 p.m.
PD Predicate disambiguation batch_69e4332155d88190b106d0dceb4554af completed April 19, 2026, 1:42 a.m.
Created at: April 10, 2026, 10:32 a.m.