Triple

T37354225
Position Surface form Disambiguated ID Type / Status
Subject Jonathan Scott as contractor E927408 entity
Predicate hasTwinCounterpart P6587 FINISHED
Object Drew Scott as real estate agent role 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: Drew Scott as real estate agent role | Statement: [Jonathan Scott as contractor, hasTwinCounterpart, Drew Scott as real estate agent role]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTwinCounterpart
Context triple: [Jonathan Scott as contractor, hasTwinCounterpart, Drew Scott as real estate agent role]
  • A. hasTwin
    Indicates that one entity is a twin of another, sharing the same birth event or time with a sibling.
  • B. hasCounterpart chosen
    Indicates that one entity corresponds to, matches, or serves as an equivalent or parallel version of another entity.
  • C. isTwinWith
    Indicates that two entities are twins, sharing the same birth parents and being born at (or very near) the same time.
  • D. hasTwinStatus
    Indicates that an entity has a twin relationship or classification, such as being one of a pair of twins or having an associated twin counterpart.
  • E. hasCounterpartName
    Indicates that an entity has an alternative or corresponding name used as its counterpart in another context, system, or representation.
  • 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_69f76eb5e034819088e53ab5b7909a68 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb8c38a9688190be524246f5682107 completed May 6, 2026, 6:45 p.m.
PD Predicate disambiguation batch_69fb5a9c6e0481908565bd849e869b24 completed May 6, 2026, 3:13 p.m.
Created at: May 3, 2026, 4:16 p.m.