Triple

T1669948
Position Surface form Disambiguated ID Type / Status
Subject Kentucky Route 84 E36100 entity
Predicate passesThrough P225 FINISHED
Object Hardin County E326217 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: Hardin County | Statement: [Kentucky Route 84, passesThrough, Hardin County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hardin County
Context triple: [Kentucky Route 84, passesThrough, Hardin County]
  • A. Hardin County chosen
    Hardin County is a county in central Kentucky known for its mix of rural communities, small cities like Elizabethtown, and its role as a regional economic and transportation hub.
  • B. Shelby County
    Shelby County is a rural county in southwestern Iowa known for its agricultural landscape and small communities.
  • C. Loudon County
    Loudon County is a county in eastern Tennessee that forms part of the Knoxville metropolitan region, known for its mix of suburban communities, rural landscapes, and access to the Tennessee River.
  • D. Butler County
    Butler County is a rural county in south-central Alabama known for its pine forests, small towns, and location along the Interstate 65 corridor.
  • E. Butler County
    Butler County is a county in western Pennsylvania, north of Pittsburgh, known for its mix of suburban communities, rural landscapes, and growing industrial and service sectors.
  • 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_69a8861286808190939afff3ce8ee31e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa624285bc8190a763e99e548a3294 completed March 6, 2026, 5:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69b224711a908190b4be9dfcd7737edd completed March 12, 2026, 2:26 a.m.
Created at: March 4, 2026, 7:29 p.m.