Triple

T17663369
Position Surface form Disambiguated ID Type / Status
Subject FIFA Player of the Century (internet poll) 2000 E440307 entity
Predicate hasGenderBiasDebate P2733 FINISHED
Object male-only award 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-only award | Statement: [FIFA Player of the Century (internet poll) 2000, hasGenderBiasDebate, male-only award]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasGenderBiasDebate
Context triple: [FIFA Player of the Century (internet poll) 2000, hasGenderBiasDebate, male-only award]
  • A. 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.
  • B. hasGenderRepresentation
    Indicates that something includes, reflects, or portrays one or more genders within its content, structure, or composition.
  • C. hasGenderFocus
    Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
  • D. hasGenderDistributionIssues chosen
    Indicates that the entity exhibits problems, imbalances, or inequities related to the distribution or representation of different genders.
  • E. hasGenderedHistoricalTerm
    Indicates that one entity is referred to by a historically used term whose form or usage is specific to a 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_69d8b9e87e18819087104a44dc4dc5b1 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e46ea7f0ec81908eff43aa845584af completed April 19, 2026, 5:56 a.m.
PD Predicate disambiguation batch_69e3cde007d8819090dd92eea9f022cc completed April 18, 2026, 6:30 p.m.
Created at: April 10, 2026, 9:51 a.m.