Triple

T4083641
Position Surface form Disambiguated ID Type / Status
Subject Oneida Lake E87537 entity
Predicate locatedInCounty P40 FINISHED
Object Oneida County E386691 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: Oneida County | Statement: [Oneida Lake, locatedInCounty, Oneida County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oneida County
Context triple: [Oneida Lake, locatedInCounty, Oneida County]
  • A. Oneida County chosen
    Oneida County is a county in central New York State, known for its seat in the city of Utica and its role as a regional economic and transportation hub.
  • 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 county in northeastern Pennsylvania known for including part of the Pocono Mountains region.
  • E. 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.
  • 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_69aed9435cf48190ad1da737c962d19d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefc7933b481909bb3e02c6c04c8ee completed March 9, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b6721847ec8190bc4307ee958d1096 completed March 15, 2026, 8:47 a.m.
Created at: March 9, 2026, 3:39 p.m.