Triple

T11803924
Position Surface form Disambiguated ID Type / Status
Subject Charlotte-Genesee Lighthouse E280695 entity
Predicate owner P347 FINISHED
Object Monroe County E328574 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: Monroe County | Statement: [Charlotte-Genesee Lighthouse, owner, Monroe County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monroe County
Context triple: [Charlotte-Genesee Lighthouse, owner, Monroe County]
  • A. Monroe County
    Monroe County is a rural county in southwestern Alabama known historically as the home of Monroeville, the hometown of author Harper Lee and a setting that inspired "To Kill a Mockingbird."
  • B. Monroe County chosen
    Monroe County is a county in the U.S. state of Michigan located along the western shore of Lake Erie, south of Detroit.
  • C. Monroe County
    Monroe County is a county in northeastern Pennsylvania known for including part of the Pocono Mountains region.
  • D. Monroe County
    Monroe County is a large, sparsely populated county in southern Florida that includes the Florida Keys and portions of the mainland, known for its coastal ecosystems, tourism, and protected natural areas.
  • E. Monroe County
    Monroe County is a rural county in southern West Virginia known for its scenic Appalachian landscapes, agriculture, and historic small towns.
  • 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_69d6ab26aae88190b2489efcb2a24234 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5a5a2048190b68027f622366079 completed April 10, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6eabf5ed88190b6de7b99b5ab590f completed May 3, 2026, 6:27 a.m.
Created at: April 8, 2026, 9:42 p.m.