Triple

T4529438
Position Surface form Disambiguated ID Type / Status
Subject Detroit Red E106258 entity
Predicate occupationDuringAlias P57269 FINISHED
Object shoeshine boy 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: shoeshine boy | Statement: [Detroit Red, occupationDuringAlias, shoeshine boy]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: occupationDuringAlias
Context triple: [Detroit Red, occupationDuringAlias, shoeshine boy]
  • A. subjectOccupation
    Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
  • B. employedRole
    Indicates that an entity holds or performs a specific role or position within an employment or work context.
  • C. occupationalNameFor
    Indicates that one entity is the name or label used to denote the occupation or profession of another entity.
  • D. earlierOccupation
    Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
  • E. occupationOf
    Indicates that one entity holds or performs the job, role, or profession associated with another entity.
  • F. None of above. chosen

Provenance (4 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_69bd43f3d6e08190a91824f833d51bbe completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd5779593081908593537b9239e01b completed March 20, 2026, 2:19 p.m.
PD Predicate disambiguation batch_69bd521cf77c819083852de3094d1377 completed March 20, 2026, 1:56 p.m.
PDg Predicate description generation batch_69bd56b3e4c88190a7ade3d0ed0ab606 completed March 20, 2026, 2:16 p.m.
Created at: March 20, 2026, 1:03 p.m.