Triple

T10808350
Position Surface form Disambiguated ID Type / Status
Subject Mayella Ewell E255025 entity
Predicate residence P75 FINISHED
Object Maycomb County E889126 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: Maycomb County | Statement: [Mayella Ewell, residence, Maycomb County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maycomb County
Context triple: [Mayella Ewell, residence, Maycomb County]
  • A. Maycomb County, Alabama chosen
    Maycomb County, Alabama is the fictional Depression-era Southern town that serves as the primary setting of Harper Lee’s novel "To Kill a Mockingbird."
  • B. Yoknapatawpha County
    Yoknapatawpha County is a fictional Mississippi county created by William Faulkner as the primary setting for many of his novels exploring the American South.
  • C. Hale County
    Hale County is a rural county in west-central Alabama known for its agricultural landscape, small towns, and role in the Black Belt region.
  • D. Hazzard County, Georgia
    Hazzard County, Georgia is a fictional rural Southern county best known as the primary setting of the television series "The Dukes of Hazzard."
  • E. Shelby County, Alabama
    Shelby County, Alabama is a suburban county in central Alabama, known for its fast-growing communities just south of Birmingham and a mix of residential, commercial, and natural areas.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d733b60c6481909b043565a65f996d completed April 9, 2026, 5:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d6a7b8c481908249acfffc97b08a completed April 18, 2026, 12:56 a.m.
Created at: April 8, 2026, 9:18 p.m.