Triple

T18380065
Position Surface form Disambiguated ID Type / Status
Subject Amy Prentiss E446418 entity
Predicate fictionalOccupationOfProtagonist P34569 FINISHED
Object chief of detectives 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: chief of detectives | Statement: [Amy Prentiss, fictionalOccupationOfProtagonist, chief of detectives]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fictionalOccupationOfProtagonist
Context triple: [Amy Prentiss, fictionalOccupationOfProtagonist, chief of detectives]
  • 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. featuresProtagonistOccupation
    Indicates that the work’s main character has a specified occupation or job role.
  • D. laterOccupationInFiction
    Indicates that a fictional character holds a particular occupation at a later point in the narrative or timeline, distinct from their earlier roles.
  • E. hasFictionalProfessionLevel
    Indicates that an entity holds a fictional or imagined profession at a specified level, rank, or degree of expertise.
  • 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_69d8b9f370b88190b1e5081c2c238e7f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e5179aa328819097f5ed8193cfa401 completed April 19, 2026, 5:57 p.m.
PD Predicate disambiguation batch_69e44ff1f92c8190afbb8e85d12bf2a9 completed April 19, 2026, 3:45 a.m.
Created at: April 10, 2026, 10:45 a.m.