Triple

T16895502
Position Surface form Disambiguated ID Type / Status
Subject Wanda Gershwitz E424288 entity
Predicate portrayedBy P1507 FINISHED
Object Jamie Lee Curtis E186111 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: Jamie Lee Curtis | Statement: [Wanda Gershwitz, portrayedBy, Jamie Lee Curtis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jamie Lee Curtis
Context triple: [Wanda Gershwitz, portrayedBy, Jamie Lee Curtis]
  • A. Jamie Lee Curtis chosen
    Jamie Lee Curtis is an American actress and author renowned for her versatile film career spanning horror classics like "Halloween" and acclaimed dramatic and comedic roles.
  • B. Dee Wallace
    Dee Wallace is an American actress best known for her role as the mother in the classic science-fiction film "E.T. the Extra-Terrestrial."
  • C. Heather Langenkamp
    Heather Langenkamp is an American actress best known for playing Nancy Thompson, the resourceful heroine of the original A Nightmare on Elm Street horror film and several of its sequels.
  • D. Kim Roberts
    Kim Roberts is a film editor known for her work on the documentary "Waiting for Superman."
  • E. Jami Gertz
    Jami Gertz is an American actress known for her roles in 1980s films and television series, including standout performances in movies like "The Lost Boys" and "Quicksilver."
  • 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_69d889da3e8c8190a2b118f383f0beac completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3c8d7aec88190888f13601acbcd77 completed April 18, 2026, 6:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7ad473081908b1c1d9524cf64a6 completed May 10, 2026, 6 p.m.
Created at: April 10, 2026, 5:29 a.m.