Triple

T9368581
Position Surface form Disambiguated ID Type / Status
Subject World Amateur Golf Ranking E225471 entity
Predicate genderCoverage P62384 FINISHED
Object male amateur golfers LITERAL 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: male amateur golfers | Statement: [World Amateur Golf Ranking, genderCoverage, male amateur golfers]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: genderCoverage
Context triple: [World Amateur Golf Ranking, genderCoverage, male amateur golfers]
  • A. genderTarget
    Indicates that an action, message, or effect is specifically directed toward entities of a particular gender.
  • B. genderEquality
    Indicates that the relationship or action promotes, reflects, or ensures equal rights, opportunities, and treatment for all genders without discrimination.
  • C. genderIntegration chosen
    Indicates the extent to which individuals of different genders are included, mixed, or participate together within a given context or system.
  • D. featuredGender
    Indicates that a particular gender is highlighted, emphasized, or given primary focus in a given context or presentation.
  • E. hasGenderNeutrality
    Indicates that something (such as a term, form, or expression) is neutral with respect to gender and does not specify or imply any particular gender.
  • 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_69ca842cbddc819099d71ecec48cf9e5 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd5080f55c8190bd5ca0dc0a4ea989 completed April 1, 2026, 5:06 p.m.
PD Predicate disambiguation batch_69cc7a6abb8c81908c7a2f4ee92cc949 completed April 1, 2026, 1:52 a.m.
Created at: March 30, 2026, 7:43 p.m.