Triple

T25708075
Position Surface form Disambiguated ID Type / Status
Subject Miss Roberts E644651 entity
Predicate workplaceFictionalStatus P14491 FINISHED
Object fictional school 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: fictional school | Statement: [Miss Roberts, workplaceFictionalStatus, fictional school]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: workplaceFictionalStatus
Context triple: [Miss Roberts, workplaceFictionalStatus, fictional school]
  • A. fictionalOccupation
    Indicates that one entity is the imaginary or narrative-based job, role, or profession attributed to another entity within a fictional context.
  • B. employerStatus
    Indicates the current employment relationship or condition between an employer and a worker, such as whether the person is actively employed, terminated, retired, or on leave.
  • C. fictionalLaborSystem
    Indicates a labor or employment system that exists only in fiction, such as in stories, games, or speculative worlds, rather than in real-world economies.
  • D. fictionalStatus chosen
    Indicates that an entity exists only in imagination or narrative and does not correspond to a real-world counterpart.
  • E. legalStatusOfWork
    Indicates the legal classification or protection status that applies to a particular work (e.g., copyrighted, public domain, licensed).
  • 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_69e77e83c8ec8190bf52fcdac4838984 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f6135293908190809e255bf6334760 completed May 2, 2026, 3:08 p.m.
PD Predicate disambiguation batch_69f611a72780819082f44e66ca2c6ac9 completed May 2, 2026, 3 p.m.
Created at: April 21, 2026, 9:06 p.m.