Triple

T2758029
Position Surface form Disambiguated ID Type / Status
Subject Afro-Bahamians E61151 entity
Predicate traditionalOccupationHistorical P17109 FINISHED
Object fishing 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: fishing | Statement: [Afro-Bahamians, traditionalOccupationHistorical, fishing]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: traditionalOccupationHistorical
Context triple: [Afro-Bahamians, traditionalOccupationHistorical, fishing]
  • A. traditionalOccupations chosen
    Indicates that an entity is associated with occupations or jobs that are customary, long-established, or culturally traditional within a particular community or context.
  • B. representedOccupation
    Indicates that one entity has served as an official or formal representative of another entity’s occupation or professional role.
  • C. earliestOccupation
    Indicates that the associated occupation is the first or earliest known job or professional role held by the person in question.
  • D. historicTradeRole
    Indicates that an entity historically functioned as a significant participant or hub in trade or commercial exchange.
  • E. earlierOccupation
    Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
  • 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_69ab4b7a85bc819094a349b84beb1f2c completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdb8ba4688190b401b6eb5b734ac6 completed March 7, 2026, 8:02 a.m.
PD Predicate disambiguation batch_69abd82de7f48190acd614f28644c6da completed March 7, 2026, 7:47 a.m.
Created at: March 6, 2026, 9:57 p.m.