Triple

T37192597
Position Surface form Disambiguated ID Type / Status
Subject When I Was a Girl I Used to Scream and Shout E921498 entity
Predicate hasCastGenderFocus P2452 FINISHED
Object primarily female characters 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: primarily female characters | Statement: [When I Was a Girl I Used to Scream and Shout, hasCastGenderFocus, primarily female characters]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCastGenderFocus
Context triple: [When I Was a Girl I Used to Scream and Shout, hasCastGenderFocus, primarily female characters]
  • A. hasGenderFocus chosen
    Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
  • B. hasLeadCharacterGender
    Indicates that the primary or lead character in a work has a specified gender.
  • C. hasGenderRole
    Indicates that an entity is associated with, or expected to perform, a particular socially defined gender-based role or set of behaviors.
  • D. hasDirectorGender
    Indicates that an entity has a director whose gender is specified by the related value.
  • E. hasPerformerGender
    Indicates that an action, event, or performance is associated with the gender of the performer who carries it out.
  • 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_69f76ea313a08190a54404cd1e47da90 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fff9b126b4819085a4cf8791d388d1 completed May 10, 2026, 3:21 a.m.
PD Predicate disambiguation batch_69fff8f913a881908d3b7e490d92631f completed May 10, 2026, 3:18 a.m.
Created at: May 3, 2026, 4:15 p.m.