Triple

T26384016
Position Surface form Disambiguated ID Type / Status
Subject Take Me or Leave Me E663224 entity
Predicate fictionalRelationshipDepicted P23406 FINISHED
Object Maureen Johnson–Joanne Jefferson relationship 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: Maureen Johnson–Joanne Jefferson relationship | Statement: [Take Me or Leave Me, fictionalRelationshipDepicted, Maureen Johnson–Joanne Jefferson relationship]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fictionalRelationshipDepicted
Context triple: [Take Me or Leave Me, fictionalRelationshipDepicted, Maureen Johnson–Joanne Jefferson relationship]
  • A. fictionalRelationship
    Indicates a relationship that exists only within a fictional or imagined context between entities.
  • B. characterActorRelationship
    Indicates a relationship where an actor portrays or is associated with a specific character in a work.
  • C. portraysCharacterRelationship
    Indicates that one entity depicts or represents the relationship between characters in another entity.
  • D. portraysRelationship chosen
    Indicates that one entity depicts, represents, or illustrates a relationship between other entities.
  • E. portraysRelation
    Indicates that one entity depicts, represents, or acts in the role of another entity within some medium or context.
  • 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_69ee88374adc81909868f3bab374a32f completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f6691f5e188190b12c7b2eb729a45e completed May 2, 2026, 9:14 p.m.
PD Predicate disambiguation batch_69f66598d6008190a7ca8ff80399fd34 completed May 2, 2026, 8:59 p.m.
Created at: April 26, 2026, 11:21 p.m.