Triple

T14636811
Position Surface form Disambiguated ID Type / Status
Subject Sweet Home men E343627 entity
Predicate associatedWithCharacter P1481 FINISHED
Object Mr. Garner E345202 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: Mr. Garner | Statement: [Sweet Home men, associatedWithCharacter, Mr. Garner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mr. Garner
Context triple: [Sweet Home men, associatedWithCharacter, Mr. Garner]
  • A. Mr. Garner chosen
    Mr. Garner is the white slave owner of Sweet Home plantation in Toni Morrison’s novel "Beloved," known for his comparatively lenient yet still oppressive treatment of the enslaved people there.
  • B. Hugh Garner
    Hugh Garner was a Canadian author best known for his socially conscious novels and short stories depicting working-class life in Toronto.
  • C. Mr. Garrett
    Mr. Garrett is a young librarian and the protagonist of M. R. James’s ghost story “The Tractate Middoth,” who becomes entangled in a sinister mystery involving an old book and a haunted inheritance.
  • D. Henry Garner
    Henry Garner is an American drummer best known for his work with the 1970s soul and funk band Rose Royce.
  • E. Bill Gunter
    Bill Gunter is an American Democratic politician from Florida who served in statewide office, including as the state’s insurance commissioner and treasurer, during the 1970s and 1980s.
  • 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_69d822dffc3c8190aa173b90761bffda completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb4aca6448190adf1042dfbfef716 completed April 14, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda934ec3c81909eb3c3a54260436b completed May 8, 2026, 9:13 a.m.
Created at: April 10, 2026, 1:26 a.m.