Triple

T21397595
Position Surface form Disambiguated ID Type / Status
Subject Felix Turner E527826 entity
Predicate fictionalDisease P143817 FINISHED
Object AIDS 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: AIDS | Statement: [Felix Turner, fictionalDisease, AIDS]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fictionalDisease
Context triple: [Felix Turner, fictionalDisease, AIDS]
  • A. fictionalDisability
    Indicates that an entity has a disability that exists only in fictional or imaginary contexts, rather than in real-world medical or social classifications.
  • B. fictionalInvention
    Indicates that one entity is an invention or creation that exists only within the fictional context of another entity (such as a story, universe, or work).
  • C. fictionalHospital
    Indicates that a hospital is imaginary or exists only within a fictional or narrative context, rather than in reality.
  • D. fictionalizationOf
    Indicates that one entity is a fictional or dramatized representation, adaptation, or reimagining of another (typically real or earlier) entity or event.
  • E. fictionalField
    Indicates that the subject is associated with a fictional or imaginary field, domain, or area rather than a real-world one.
  • F. None of above. chosen

Provenance (4 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_69e0b520ee3c8190abddbee7e37e834c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b16a9c7c819083bd2d298106fdf1 completed April 22, 2026, 11:30 a.m.
PD Predicate disambiguation batch_69e61633f8208190a2a849457c4e4198 completed April 20, 2026, 12:04 p.m.
PDg Predicate description generation batch_69e6190163448190a2404b396215c686 completed April 20, 2026, 12:16 p.m.
Created at: April 16, 2026, 5:14 p.m.