Triple

T15481176
Position Surface form Disambiguated ID Type / Status
Subject Catherine Barkley E376919 entity
Predicate emotionalBackground P87208 FINISHED
Object grieving former fiancé killed in war 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: grieving former fiancé killed in war | Statement: [Catherine Barkley, emotionalBackground, grieving former fiancé killed in war]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: emotionalBackground
Context triple: [Catherine Barkley, emotionalBackground, grieving former fiancé killed in war]
  • A. emotionalTrajectory
    Indicates how an entity’s emotional state changes or progresses over time in relation to another entity or context.
  • B. emotionalCoreOf
    Indicates that one entity serves as the central source, essence, or primary driver of another entity’s emotional character or experience.
  • C. emotionalTrait chosen
    Indicates that an entity possesses a particular emotional characteristic, disposition, or affective quality.
  • D. emotionalDynamic
    Indicates how emotions, moods, or affective states change, interact, or influence each other between entities over time.
  • E. loveInterestFamilyBackground
    Indicates that information is being provided about the family background of a person's romantic partner or love interest.
  • 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_69d85cd21dcc81908646251b1c26ea00 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f8cb4388190a3b4c92c3bb4ad4f completed April 16, 2026, 1:46 a.m.
PD Predicate disambiguation batch_69ded2874b788190999158e0f043be21 completed April 14, 2026, 11:49 p.m.
Created at: April 10, 2026, 3:34 a.m.