Triple

T35924989
Position Surface form Disambiguated ID Type / Status
Subject First Lady of Illinois E1038994 entity
Predicate isSpouseOfOfficeHolder P37617 FINISHED
Object Governor of Illinois 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: Governor of Illinois | Statement: [First Lady of Illinois, isSpouseOfOfficeHolder, Governor of Illinois]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: isSpouseOfOfficeHolder
Context triple: [First Lady of Illinois, isSpouseOfOfficeHolder, Governor of Illinois]
  • A. spouseLaterOffice
    Indicates that one person’s spouse held a particular office or position at a later time than the person in question.
  • B. spouseOffice
    Indicates that one entity holds an office or position that is associated with, or held by, the spouse of another entity.
  • C. hasSpousePositionInFamily
    Indicates that a person’s spouse holds a specific role or position within the family structure.
  • D. spouseOfOfficeholderNumber
    Indicates that one entity is the spouse of a specific officeholder identified by their ordinal number in holding a particular office.
  • E. spouseOfOfficeHolderJurisdiction chosen
    Indicates that one person is the spouse of a public office holder, with the relationship specifically tied to the jurisdiction in which that office is held.
  • 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_69f76e2320748190b7f5c4750d0cd0d3 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7ac23d1388190bdf9628b294943bd completed May 3, 2026, 8:12 p.m.
PD Predicate disambiguation batch_69f7ab734d848190a84f9b8c3a952b75 completed May 3, 2026, 8:09 p.m.
Created at: May 3, 2026, 4:07 p.m.