Triple

T21511246
Position Surface form Disambiguated ID Type / Status
Subject Hush...Hush, Sweet Charlotte E530724 entity
Predicate screenwriter P2831 FINISHED
Object Henry Farrell NE NERFINISHED

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: Henry Farrell | Statement: [Hush...Hush, Sweet Charlotte, screenwriter, Henry Farrell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Henry Farrell
Context triple: [Hush...Hush, Sweet Charlotte, screenwriter, Henry Farrell]
  • A. Henry Farrell chosen
    Henry Farrell was an American novelist and screenwriter best known for his psychological horror and suspense stories, including the novel that inspired the film "What Ever Happened to Baby Jane?".
  • B. Theodore West
    Theodore West is a rural locality within Queensland’s Banana Shire, known for its agricultural landscape and small-community character.
  • C. George Eldredge
    George Eldredge was an American character actor known for his numerous supporting roles in mid-20th-century film and television, often portraying authority figures or villains.
  • D. George Hackathorne
    George Hackathorne was an American silent film actor active in the 1910s and 1920s, known for his roles in early Hollywood productions.
  • E. Guy Farley
    Guy Farley is a British film composer known for his work on a variety of feature films, television projects, and commercials.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c45c81f08190a6b8bbb70a45aae7 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea863b18819080e3ff249b10ec28 completed April 23, 2026, 9:46 a.m.
Created at: April 16, 2026, 6:25 p.m.