Triple

T11094007
Position Surface form Disambiguated ID Type / Status
Subject The Good Nurse E262326 entity
Predicate stars P1956 FINISHED
Object Eddie Redmayne E106298 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: Eddie Redmayne | Statement: [The Good Nurse, stars, Eddie Redmayne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eddie Redmayne
Context triple: [The Good Nurse, stars, Eddie Redmayne]
  • A. Eddie Redmayne chosen
    Eddie Redmayne is an English actor acclaimed for his transformative performances in film and theatre, including his Oscar-winning role in "The Theory of Everything."
  • B. James McAvoy
    James McAvoy is a Scottish actor known for his versatile performances in films such as the X-Men series, Atonement, and Split.
  • C. Ben Whishaw
    Ben Whishaw is an English actor known for his versatile performances in film, television, and theatre, including roles such as Q in the James Bond series and the voice of Paddington Bear.
  • D. Benedict Cumberbatch
    Benedict Cumberbatch is an acclaimed English actor known for his roles in the television series "Sherlock" and films such as "The Imitation Game" and the Marvel Cinematic Universe's "Doctor Strange."
  • E. Rafe Spall
    Rafe Spall is an English actor known for his roles in films such as "Life of Pi," "The Big Short," and "Hot Fuzz," as well as various television and stage productions.
  • 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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d799ed12d88190a4ad8c346d68f11f completed April 9, 2026, 12:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e7e0c7e4819098e690ffebbd8e61 completed April 18, 2026, 8:21 p.m.
Created at: April 8, 2026, 9:27 p.m.