Triple

T36078652
Position Surface form Disambiguated ID Type / Status
Subject Kevin Pollak as Janni Gogolak E1043568 entity
Predicate hasFamilyRelationInStory P184664 FINISHED
Object father of Yanni Gogolak 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: father of Yanni Gogolak | Statement: [Kevin Pollak as Janni Gogolak, hasFamilyRelationInStory, father of Yanni Gogolak]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFamilyRelationInStory
Context triple: [Kevin Pollak as Janni Gogolak, hasFamilyRelationInStory, father of Yanni Gogolak]
  • A. hasSiblingInStory
    Indicates that one character in a narrative has at least one sibling who also appears within the same story.
  • B. hasFamilyRelationContext
    Indicates that there exists a family-based relationship or kinship context connecting the referenced entities.
  • C. storylineFamilyMember chosen
    Indicates that one character is related to another as a family member within the context of a storyline or narrative.
  • D. hasAffiliationInStory
    Indicates that one entity is affiliated with, associated with, or connected to another entity within the context of a specific story or narrative.
  • E. associatedWithPersonInStory
    Indicates that one entity has a connection or involvement with a specific person within the context of a story.
  • 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_69f76e3154908190a6f702671c2bea08 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69fe5ec9028081909ae3d6fbe2f4cbbc completed May 8, 2026, 10:08 p.m.
PD Predicate disambiguation batch_69fe5e1d715881909fc516fafc707644 completed May 8, 2026, 10:05 p.m.
Created at: May 3, 2026, 4:08 p.m.