Triple

T1228172
Position Surface form Disambiguated ID Type / Status
Subject George Sutherland E26373 entity
Predicate workLocation P7 FINISHED
Object Utah E22720 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: Utah | Statement: [George Sutherland, workLocation, Utah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Utah
Context triple: [George Sutherland, workLocation, Utah]
  • A. Utah chosen
    Utah is a landlocked state in the western United States known for its vast deserts, distinctive red rock landscapes, and prominent national parks such as Zion and Arches.
  • B. Idaho
    Idaho is a mountainous, landlocked state in the northwestern United States known for its vast wilderness areas, outdoor recreation, and significant agricultural production, especially potatoes.
  • C. Nevada
    Nevada is a western U.S. state known for its vast deserts, legalized gambling, and the entertainment hub of Las Vegas.
  • D. Nevada
    Nevada is a small city in western Missouri known as the county seat of Vernon County and for its historic downtown and regional agricultural economy.
  • E. Colorado
    Colorado is a landlocked U.S. state known for its Rocky Mountain landscapes, outdoor recreation, and cities like Denver and Boulder.
  • 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_69a49484688c8190a1bf285eb396a8b6 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be3c5d4c819087f9e9e37204c3be completed March 1, 2026, 10:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69aebee55ea4819097baa92110f35769 completed March 9, 2026, 12:36 p.m.
Created at: March 1, 2026, 7:47 p.m.