Triple

T10560003
Position Surface form Disambiguated ID Type / Status
Subject Olympic College E249190 entity
Predicate regionServed P82 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: [Olympic College, regionServed, Mason County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mason County
Context triple: [Olympic College, regionServed, 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_69d381c8bd708190acf3d275c908251e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d5271f3c6c819080b49fbe3aa09e09 completed April 7, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69d98832b97c8190a11246e087674e57 completed April 10, 2026, 11:30 p.m.
Created at: April 6, 2026, 12:35 p.m.