Triple

T7958837
Position Surface form Disambiguated ID Type / Status
Subject Goldfield, Nevada E184808 entity
Predicate county P75 FINISHED
Object Esmeralda County E30814 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: Esmeralda County | Statement: [Goldfield, Nevada, county, Esmeralda County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Esmeralda County
Context triple: [Goldfield, Nevada, county, Esmeralda County]
  • A. Esmeralda County chosen
    Esmeralda County is a sparsely populated rural county in western Nevada known for its historic mining towns and vast desert landscapes.
  • B. Louisa County
    Louisa County is a rural county in southeastern Iowa known for its agricultural landscape and small communities along the Iowa and Mississippi rivers.
  • C. Louisa County
    Louisa County is a largely rural county in central Virginia known for its small towns, agricultural landscape, and proximity to Lake Anna.
  • D. Castro County
    Castro County is a rural county in the Texas Panhandle known for its agriculture-based economy and small communities.
  • E. Marengo County
    Marengo County is a rural county in west-central Alabama known for its agricultural economy, historic small towns, and location in the state's Black Belt region.
  • 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_69ca8293a2388190aace944d7ed9c0c0 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3b80050c81909b2db95ade495052 completed March 31, 2026, 3:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc937e687081908ae33ae7335d685e completed April 1, 2026, 3:39 a.m.
Created at: March 30, 2026, 5:11 p.m.