Triple

T17983820
Position Surface form Disambiguated ID Type / Status
Subject Franklin County E430172 entity
Predicate hasBorderWith P224 FINISHED
Object Grant County NE NERFINISHED

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: Grant County | Statement: [Franklin County, hasBorderWith, Grant County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grant County
Context triple: [Franklin County, hasBorderWith, Grant County]
  • A. Grant County chosen
    Grant County is a county in central Washington State known for its agricultural production, reservoirs, and outdoor recreation areas.
  • B. Grant County
    Grant County is a rural county in eastern West Virginia known for its mountainous terrain, outdoor recreation areas, and small communities.
  • C. Grant County
    Grant County is a county in east-central Indiana known for its small towns, agricultural landscape, and historical ties to figures like James Dean.
  • D. Mason County
    Mason County is a county in western Washington State known for its forests, waterways, and location along the southern reaches of Puget Sound.
  • E. Mason County
    Mason County is a rural county in central Texas known for its ranching, hunting, and the historic town of Mason.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b90364248190a37381adea932f42 completed April 10, 2026, 8:46 a.m.
NER Named-entity recognition batch_69e4b2992fe481908c0d2757b4de5bad completed April 19, 2026, 10:46 a.m.
Created at: April 10, 2026, 10:23 a.m.