Triple

T9836139
Position Surface form Disambiguated ID Type / Status
Subject Puget Sound islands E239105 entity
Predicate hasCounty P285 FINISHED
Object Mason County E44266 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: Mason County | Statement: [Puget Sound islands, hasCounty, Mason County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mason County
Context triple: [Puget Sound islands, hasCounty, Mason County]
  • A. Mason County chosen
    Mason County is a county in western Washington State known for its forests, waterways, and location along the southern reaches of Puget Sound.
  • B. Grant County
    Grant County is a county in central Washington State known for its agricultural production, reservoirs, and outdoor recreation areas.
  • C. Grant County
    Grant County is a rural county in eastern West Virginia known for its mountainous terrain, outdoor recreation areas, and small communities.
  • D. Lewis County
    Lewis County is a county in southwestern Washington State known for its rural communities, forests, and position between the Cascade Range and the Pacific Coast.
  • E. Lewis County
    Lewis County is a rural county in north-central Idaho known for its agricultural communities, forested landscapes, and small-town character.
  • 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_69ca84e314108190978324a4bdb959f8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb33b07688190b78a70cf535c3efc completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d32a5921c8819085a2188805b4811c completed April 6, 2026, 3:36 a.m.
Created at: March 30, 2026, 8:33 p.m.