Triple

T10335798
Position Surface form Disambiguated ID Type / Status
Subject KEYW E242998 entity
Predicate operator P179 FINISHED
Object Monroe County unclear NED1 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: [KEYW, operator, Monroe County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monroe County
Context triple: [KEYW, operator, Monroe County]
  • A. 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.
  • B. Monroe County
    Monroe County is a rural county in southern West Virginia known for its scenic Appalachian landscapes, agriculture, and historic small towns.
  • C. 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."
  • D. Monroe County
    Monroe County is a populous county in western New York State that includes the city of Rochester and serves as a regional center for education, culture, and industry.
  • E. Monroe County
    Monroe County is a county in northeastern Pennsylvania known for including part of the Pocono Mountains region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69d381af787481908bc401325c760a88 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4dfc425748190a3d29f81e32e948b completed April 7, 2026, 10:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69d94aec37288190bd9060ba39ec4df2 completed April 10, 2026, 7:09 p.m.
Created at: April 6, 2026, 11:53 a.m.