Triple

T2961616
Position Surface form Disambiguated ID Type / Status
Subject Ephrata E80061 entity
Predicate partOf P40 FINISHED
Object Grant County E412059 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: Grant County | Statement: [Ephrata, partOf, Grant County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grant County
Context triple: [Ephrata, partOf, 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. 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.
  • C. Clinton County
    Clinton County is the name of numerous counties in the United States, typically named after prominent American statesmen such as George Clinton or DeWitt Clinton.
  • D. Marshall County
    Marshall County is a county in northern Alabama known for its scenic location around Lake Guntersville and its mix of small towns and rural communities.
  • E. Murray County
    Murray County is a county in northwestern Georgia, United States, known for its location in the Appalachian foothills and its historical ties to early Cherokee Nation lands.
  • 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_69ad8b1341848190bd19dbf46892887d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad995454448190834aa5d47a4ed5ac completed March 8, 2026, 3:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f0432e081908110ede1c2b7a54a completed March 14, 2026, 3:30 p.m.
Created at: March 8, 2026, 2:57 p.m.