Triple

T5143814
Position Surface form Disambiguated ID Type / Status
Subject Human Resistance E116020 entity
Predicate hasNotableMember P304 FINISHED
Object Kate Brewster E498090 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: Kate Brewster | Statement: [Human Resistance, hasNotableMember, Kate Brewster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kate Brewster
Context triple: [Human Resistance, hasNotableMember, Kate Brewster]
  • A. Kate Brewster chosen
    Kate Brewster is a key character in the Terminator franchise, a veterinarian who becomes John Connor’s future wife and a leader in the human resistance against Skynet.
  • B. Kate Garvey
    Kate Garvey is a British public relations executive and former political aide, known for her work with Tony Blair and her marriage to Wikipedia co-founder Jimmy Wales.
  • C. Betsy Blair
    Betsy Blair was an American actress best known for her acclaimed, Oscar-nominated performance in the 1955 film "Marty" and for her work in both Hollywood and European cinema.
  • D. Betsy Rue
    Betsy Rue is an American actress best known for her roles in horror and thriller films, including her appearance in the slasher movie "My Bloody Valentine 3D."
  • E. Kate Burroughs
    Kate Burroughs is the central protagonist of the film "The Four Seasons," around whom the story’s relationships and events revolve.
  • 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_69bd4446c0e08190a7c29dc74976bf03 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7883004881909c763da818d9b6e2 completed March 20, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69beefa31458819094b53cbc7a2f5677 completed March 21, 2026, 7:21 p.m.
Created at: March 20, 2026, 1:43 p.m.