Triple

T16531838
Position Surface form Disambiguated ID Type / Status
Subject Mount Charleston E401585 entity
Predicate county P75 FINISHED
Object Clark County E27728 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: Clark County | Statement: [Mount Charleston, county, Clark County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Clark County
Context triple: [Mount Charleston, county, Clark County]
  • A. Clark County chosen
    Clark County is the most populous county in Nevada and includes the city of Las Vegas, serving as a major hub for tourism and entertainment.
  • B. Clark County
    Clark County is a county in southwestern Washington State that includes communities such as La Center and the city of Vancouver within the Portland metropolitan area.
  • C. Clark County
    Clark County is a rural county in central Wisconsin known for its agriculture, forests, and small communities.
  • D. Clark County
    Clark County is a local governmental jurisdiction in the United States that administers regional services, law, and infrastructure for its residents.
  • E. Clark County, Nevada
    Clark County, Nevada is the populous southern Nevada county that includes the Las Vegas metropolitan area and serves as a major hub for tourism, entertainment, and gaming.
  • 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_69d883838abc8190bc79cb2d41733ce2 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32ed8075c81908ff47396879abd0c completed April 18, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0067a913388190afebe40fcc42e731 completed May 10, 2026, 11:10 a.m.
Created at: April 10, 2026, 5:15 a.m.