Triple

T1705386
Position Surface form Disambiguated ID Type / Status
Subject Ioannis Kolettis E36860 entity
Predicate hasOccupationBackground P28984 FINISHED
Object doctor before entering politics 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: doctor before entering politics | Statement: [Ioannis Kolettis, hasOccupationBackground, doctor before entering politics]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasOccupationBackground
Context triple: [Ioannis Kolettis, hasOccupationBackground, doctor before entering politics]
  • A. hasFamilyBackgroundIn
    Indicates that an entity comes from, or is associated with, a particular familial or ancestral background.
  • B. hasAcademicBackgroundIn
    Indicates that an entity possesses formal education, training, or scholarly experience in a specified academic field or discipline.
  • C. earlierOccupation chosen
    Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
  • D. hasBackground
    Indicates that an entity possesses or is associated with a particular background, such as context, setting, or prior circumstances.
  • E. hadOccupationStatusUntil
    Indicates that an entity held a particular occupational status up to, but not necessarily beyond, a specified point in time.
  • 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_69a88617439c819094ffb5d16a0f6307 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69ab75ad24408190814069e6e3ef9e59 completed March 7, 2026, 12:47 a.m.
PD Predicate disambiguation batch_69aa61bad17c8190861b92cfb423f68f completed March 6, 2026, 5:10 a.m.
Created at: March 4, 2026, 7:30 p.m.