Triple

T14954570
Position Surface form Disambiguated ID Type / Status
Subject Joan Hambling E372886 entity
Predicate hasColleague P398 FINISHED
Object Yaz McKay E340911 NE 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: Yaz McKay | Statement: [Joan Hambling, hasColleague, Yaz McKay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yaz McKay
Context triple: [Joan Hambling, hasColleague, Yaz McKay]
  • A. Yaz McKay chosen
    Yaz McKay is a character from the television series "The Chair," involved in the academic and personal dramas surrounding an English department at a struggling university.
  • B. Kimber Henry
    Kimber Henry is a central character in the TV drama "Nip/Tuck," known for her tumultuous relationships, modeling career, and complex personal struggles.
  • C. Drew Van Acker
    Drew Van Acker is an American actor best known for his roles on television series such as "Pretty Little Liars" and "Devious Maids."
  • D. Mackenzie Mauzy
    Mackenzie Mauzy is an American actress and singer known for her work on Broadway and in film and television, including her role as Rapunzel in the 2014 musical fantasy film "Into the Woods."
  • E. Drew Gehling
    Drew Gehling is an American stage and screen actor best known for originating the role of Dr. Pomatter in the Broadway musical "Waitress."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d85cca979481908747d2a81eba1cea completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded6cb336c8190b8a55106fa8fc500 completed April 15, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e9c71cc8190aff9165a6f97981a completed May 9, 2026, 12:23 a.m.
Created at: April 10, 2026, 2:40 a.m.