Triple

T25907456
Position Surface form Disambiguated ID Type / Status
Subject Russell Henderson E652790 entity
Predicate occupationBeforeCrime P29064 FINISHED
Object roofing worker 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: roofing worker | Statement: [Russell Henderson, occupationBeforeCrime, roofing worker]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: occupationBeforeCrime
Context triple: [Russell Henderson, occupationBeforeCrime, roofing worker]
  • A. earlierOccupation
    Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
  • B. hasPerpetratorOccupation chosen
    Indicates that the occupation or job role of the perpetrator involved in an act or incident is being specified.
  • C. occupationType
    Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
  • D. subjectOccupation
    Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
  • E. hasPastOccupation
    Indicates that an entity previously held a particular job, role, or occupation in the past.
  • 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_69e7ab3d3f8481909bc53ed64c06af33 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f61f12b0f08190bc4a16907941864c completed May 2, 2026, 3:58 p.m.
PD Predicate disambiguation batch_69f61b37a5648190b10d33ae205ccfee completed May 2, 2026, 3:41 p.m.
Created at: April 22, 2026, 8:27 a.m.