Triple

T6812975
Position Surface form Disambiguated ID Type / Status
Subject The Farmer Takes a Wife (1935 film) E156680 entity
Predicate mainCharacter P1183 FINISHED
Object Dan Harrow E646839 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: Dan Harrow | Statement: [The Farmer Takes a Wife (1935 film), mainCharacter, Dan Harrow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dan Harrow
Context triple: [The Farmer Takes a Wife (1935 film), mainCharacter, Dan Harrow]
  • A. Dan Harrow chosen
    Dan Harrow is the earnest, idealistic young farmer who serves as the central romantic lead in the stage musical and film "The Farmer Takes a Wife."
  • B. Dan Talbot
    Dan Talbot was an influential American film distributor and exhibitor known for championing foreign and independent cinema in the United States.
  • C. Neil Hartley
    Neil Hartley is a film and television producer known for his work on the adaptation of "The Go-Between."
  • D. Michael Krieger
    Michael Krieger is a fictional character appearing in the story of "Watch Over Me."
  • E. Scott Gorham
    Scott Gorham is an American guitarist best known for his long tenure with the hard rock band Thin Lizzy and later work with its successor projects.
  • 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_69c68828b26c819090fe9df7612bbc27 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d329861881909f65bd1017ea384b completed March 27, 2026, 6:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7bf6c62948190a8e8f0d8f259ba42 completed March 28, 2026, 11:45 a.m.
Created at: March 27, 2026, 2:17 p.m.