Triple

T1108002
Position Surface form Disambiguated ID Type / Status
Subject Into the Woods (2014 film) E25529 entity
Predicate stars P1956 FINISHED
Object Johnny Depp E18986 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: Johnny Depp | Statement: [Into the Woods (2014 film), stars, Johnny Depp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johnny Depp
Context triple: [Into the Woods (2014 film), stars, Johnny Depp]
  • A. Johnny Depp chosen
    Johnny Depp is an American actor known for his eclectic, often eccentric roles in films such as the "Pirates of the Caribbean" series, "Edward Scissorhands," and numerous collaborations with director Tim Burton.
  • B. Nicolas Cage
    Nicolas Cage is an American actor known for his intense and eclectic performances across action, drama, and independent films.
  • C. Val Kilmer
    Val Kilmer is an American actor known for his versatile performances in films such as "Top Gun," "The Doors," and "Batman Forever."
  • D. Guy Pearce
    Guy Pearce is an Australian actor known for his versatile performances in films such as "Memento," "L.A. Confidential," and "The King's Speech."
  • E. Burn Gorman
    Burn Gorman is a British-American actor known for his character roles in film and television, including appearances in projects like "Torchwood," "Game of Thrones," and "Pacific Rim."
  • 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_69a49428d4448190b3b36991ceae87ce completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b9e47e4881908928900df72781f0 completed March 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c4cee1881909ca8af01f22bb8bb completed March 7, 2026, 4:03 p.m.
Created at: March 1, 2026, 7:43 p.m.