Triple

T24046487
Position Surface form Disambiguated ID Type / Status
Subject Ray McElrathbey E595533 entity
Predicate hasThemeInLifeStory P76865 FINISHED
Object family responsibility 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: family responsibility | Statement: [Ray McElrathbey, hasThemeInLifeStory, family responsibility]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasThemeInLifeStory
Context triple: [Ray McElrathbey, hasThemeInLifeStory, family responsibility]
  • A. hasThemeInStory chosen
    Indicates that a particular theme is present or plays a significant role within a given story.
  • B. hasPersonalThemes
    Indicates that something (such as a work, message, or expression) involves themes that are personal, intimate, or directly related to an individual’s own experiences or inner life.
  • C. hasPartInLife
    Indicates that an entity participates in, contributes to, or plays a role within some aspect or period of another entity’s life.
  • D. hasBiographicalTheme
    Indicates that something (such as a work, text, or content) centers on or significantly involves biographical subject matter, such as a person’s life, experiences, or personal history.
  • E. hasSayingTheme
    Indicates that a saying, proverb, or quoted expression is about or centers on a particular theme or subject.
  • 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_69e288c06a908190899cad4531f32c9a completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1d9ca5a18819086da68b69eed8cc1 completed April 29, 2026, 10:13 a.m.
PD Predicate disambiguation batch_69f1764345388190a3102b62ddb729b4 completed April 29, 2026, 3:08 a.m.
Created at: April 17, 2026, 10:16 p.m.