Triple

T12997705
Position Surface form Disambiguated ID Type / Status
Subject Angel Evangelista E322081 entity
Predicate storyArcIncludes P39504 FINISHED
Object transition from sex work to professional modeling 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: transition from sex work to professional modeling | Statement: [Angel Evangelista, storyArcIncludes, transition from sex work to professional modeling]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: storyArcIncludes
Context triple: [Angel Evangelista, storyArcIncludes, transition from sex work to professional modeling]
  • A. storyElement
    Indicates that one entity functions as a narrative component or part within the structure of another entity’s story.
  • B. notableStoryArc chosen
    Indicates that there exists a significant or prominent narrative storyline or plot development involving the subject.
  • C. stakesInStory
    Indicates that one entity has a personal investment, risk, or potential gain/loss tied to the outcome of another entity’s story or narrative.
  • D. storyEngine
    Indicates that one entity functions as a narrative-generating or plot-controlling mechanism for another entity or set of events.
  • E. storyline
    Indicates that one entity serves as the narrative plot or sequence of events associated with another entity.
  • 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_69d8076479b8819090afce3591939cdf completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e7980288190a9fe629a8cc76a52 completed April 10, 2026, 10:49 p.m.
PD Predicate disambiguation batch_69d97dc153a081909d13a694993f074a completed April 10, 2026, 10:46 p.m.
Created at: April 9, 2026, 8:46 p.m.