Triple

T5005507
Position Surface form Disambiguated ID Type / Status
Subject Madison Cawthorn E112479 entity
Predicate hasParticularAgeDistinction P29430 FINISHED
Object one of the youngest members of the 117th United States Congress 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: one of the youngest members of the 117th United States Congress | Statement: [Madison Cawthorn, hasParticularAgeDistinction, one of the youngest members of the 117th United States Congress]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasParticularAgeDistinction
Context triple: [Madison Cawthorn, hasParticularAgeDistinction, one of the youngest members of the 117th United States Congress]
  • A. containsAge
    Indicates that one entity includes or specifies the age value or age-related information of another entity.
  • B. hasAge
    Indicates that an entity possesses a specific age value, typically expressed as a number of time units since its birth or creation.
  • C. hasRelativeAge
    Indicates that one entity has an age that is defined or compared in relation to the age of another entity.
  • D. hasAgeFocus chosen
    Indicates a relationship where something is characterized or distinguished by a particular age group or age-related emphasis.
  • E. ageStatus
    Indicates the relationship between an entity and its classification into an age-related category or status (e.g., minor, adult, senior).
  • 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_69bd4433d0b08190877e83959ef40d81 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd730a7590819088ab8d49c5c88c2f completed March 20, 2026, 4:17 p.m.
PD Predicate disambiguation batch_69bd714cbc448190aa53a8a83d768b64 completed March 20, 2026, 4:09 p.m.
Created at: March 20, 2026, 1:35 p.m.