Triple

T35622123
Position Surface form Disambiguated ID Type / Status
Subject Ali E1029342 entity
Predicate partnerAgeDifference P125146 FINISHED
Object significantly younger than Emmi Kurowski 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: significantly younger than Emmi Kurowski | Statement: [Ali, partnerAgeDifference, significantly younger than Emmi Kurowski]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: partnerAgeDifference
Context triple: [Ali, partnerAgeDifference, significantly younger than Emmi Kurowski]
  • A. spouseAgeDifference
    Indicates the age gap between two individuals who are spouses in a marital relationship.
  • B. relativeAgeInference
    Indicates an inferred ordering of ages between entities, specifying which one is relatively older or younger based on available information.
  • C. relativeAgeStatus chosen
    Indicates a comparative relationship specifying how the age of one entity relates to the age of another (e.g., older, younger, or same age).
  • D. hasRelativeAge
    Indicates that one entity has an age that is defined or compared in relation to the age of another entity.
  • E. ageCorrelation
    Indicates a statistical relationship between the ages of two entities, showing how changes in one entity’s age are associated with changes in the other’s.
  • 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_69f76e0709408190bbe322bf1707ef6b completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7aa699d68819081ed363931894ab3 completed May 3, 2026, 8:04 p.m.
PD Predicate disambiguation batch_69f7a8cec6d48190bebfa884b2f938c0 completed May 3, 2026, 7:58 p.m.
Created at: May 3, 2026, 4:05 p.m.