Triple

T23979289
Position Surface form Disambiguated ID Type / Status
Subject Cora Corman E604460 entity
Predicate fictionalProfessionLevel P116932 FINISHED
Object superstar 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: superstar | Statement: [Cora Corman, fictionalProfessionLevel, superstar]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fictionalProfessionLevel
Context triple: [Cora Corman, fictionalProfessionLevel, superstar]
  • A. hasFictionalProfessionLevel chosen
    Indicates that an entity holds a fictional or imagined profession at a specified level, rank, or degree of expertise.
  • B. fictionalProfessionSpecialty
    Indicates that a fictional character’s professional role is specialized in a particular subfield, focus area, or niche within that profession.
  • C. fictionalOccupation
    Indicates that one entity is the imaginary or narrative-based job, role, or profession attributed to another entity within a fictional context.
  • D. fictionalizationLevel
    Indicates the degree to which an event, account, or representation has been altered, embellished, or invented relative to factual reality.
  • E. laterOccupationInFiction
    Indicates that a fictional character holds a particular occupation at a later point in the narrative or timeline, distinct from their earlier roles.
  • 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_69e29543f40c819087700b7a272afb60 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1d2bc79688190bc98a2d57b91f5a3 completed April 29, 2026, 9:43 a.m.
PD Predicate disambiguation batch_69f161578d54819084a8b35496299993 completed April 29, 2026, 1:39 a.m.
Created at: April 17, 2026, 9:26 p.m.