Triple

T13695427
Position Surface form Disambiguated ID Type / Status
Subject Bert Girigorie E328371 entity
Predicate hasMediaAttentionReason P35413 FINISHED
Object former husband of Wendy Williams 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: former husband of Wendy Williams | Statement: [Bert Girigorie, hasMediaAttentionReason, former husband of Wendy Williams]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMediaAttentionReason
Context triple: [Bert Girigorie, hasMediaAttentionReason, former husband of Wendy Williams]
  • A. hasNotablePublicityReason
    Indicates that an entity is associated with a specific reason or event that has led to notable public attention or publicity.
  • B. mediaAttentionLevel
    Indicates the degree or intensity of attention or coverage that media outlets give to a particular subject or entity.
  • C. hasMediaCoverageSince
    Indicates that an entity has had media coverage starting from a specified point in time and continuing from then onward.
  • D. hasMediaCoverageTopic
    Indicates that a piece of media coverage is about, focused on, or thematically related to a particular topic.
  • E. mediaCoverageReason chosen
    Indicates the reason or justification for which a particular subject, event, or entity is being covered or reported on by the media.
  • 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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc8773f388190b2413b1e05fd5fd7 completed April 12, 2026, 4:29 p.m.
PD Predicate disambiguation batch_69dbbe9059488190a8113177c83e1481 completed April 12, 2026, 3:47 p.m.
Created at: April 9, 2026, 9:54 p.m.