Triple

T33636466
Position Surface form Disambiguated ID Type / Status
Subject Cullen Post E861709 entity
Predicate fictionalProfessionCombination P34569 FINISHED
Object lawyer and minister 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: lawyer and minister | Statement: [Cullen Post, fictionalProfessionCombination, lawyer and minister]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fictionalProfessionCombination
Context triple: [Cullen Post, fictionalProfessionCombination, lawyer and minister]
  • A. fictionalOccupation chosen
    Indicates that one entity is the imaginary or narrative-based job, role, or profession attributed to another entity within a fictional context.
  • B. fictionalProfessionSpecialty
    Indicates that a fictional character’s professional role is specialized in a particular subfield, focus area, or niche within that profession.
  • C. creativeRole
    Indicates that an entity holds a specific creative function or responsibility in relation to another entity, such as a work or project.
  • D. hasFictionalProfessionLevel
    Indicates that an entity holds a fictional or imagined profession at a specified level, rank, or degree of expertise.
  • 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_69f3498280c48190bcc3494017d14234 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69fe87b609888190913b0c3f787ecdba completed May 9, 2026, 1:02 a.m.
PD Predicate disambiguation batch_69fe8731af48819092084f6f74bf052d completed May 9, 2026, 1 a.m.
Created at: May 1, 2026, 1:42 a.m.