Triple

T983403
Position Surface form Disambiguated ID Type / Status
Subject Baker E21223 entity
Predicate relatedOccupation P19085 FINISHED
Object baker 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: baker | Statement: [Baker, relatedOccupation, baker]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: relatedOccupation
Context triple: [Baker, relatedOccupation, baker]
  • A. relatedProfession chosen
    Indicates that two entities have professions that are connected or associated in some meaningful way, such as being in the same field, industry, or professional domain.
  • B. subjectOccupation
    Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
  • C. representedOccupation
    Indicates that one entity has served as an official or formal representative of another entity’s occupation or professional role.
  • D. requiredOccupationOf
    Indicates that one entity specifies the occupation or job role that is required or expected for another entity (such as a position, task, or qualification).
  • E. workRelatedTo
    Indicates a relationship where one entity’s work, tasks, or professional activities are connected, associated, or relevant to those of another entity.
  • 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_69a493c383dc8190a03257f22d4b4183 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b493f5dc819090d239c2f7e083de completed March 1, 2026, 9:50 p.m.
PD Predicate disambiguation batch_69a4b2aa219081908a6b0ef786b4aa52 completed March 1, 2026, 9:42 p.m.
Created at: March 1, 2026, 7:41 p.m.