Triple

T23096737
Position Surface form Disambiguated ID Type / Status
Subject Hubert Bonisseur de La Bath E575910 entity
Predicate fictionalProfessionDetail P34569 FINISHED
Object spy for the SDECE 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: spy for the SDECE | Statement: [Hubert Bonisseur de La Bath, fictionalProfessionDetail, spy for the SDECE]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fictionalProfessionDetail
Context triple: [Hubert Bonisseur de La Bath, fictionalProfessionDetail, spy for the SDECE]
  • 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. hasFictionalProfessionLevel
    Indicates that an entity holds a fictional or imagined profession at a specified level, rank, or degree of expertise.
  • D. portraysProfession
    Indicates that one entity depicts or represents another entity in a specific profession or occupational role.
  • 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_69e245c060b48190a9bd61a47a16db17 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18de522e48190a37e6c2fda2de465 completed April 29, 2026, 4:49 a.m.
PD Predicate disambiguation batch_69ef89e5ce748190b2c3ac3843484127 completed April 27, 2026, 4:08 p.m.
Created at: April 17, 2026, 3:57 p.m.