Triple

T343605
Position Surface form Disambiguated ID Type / Status
Subject Mount Diablo meridian E6889 entity
Predicate jurisdiction P82 FINISHED
Object State of Nevada E2834 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: State of Nevada | Statement: [Mount Diablo meridian, jurisdiction, State of Nevada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: State of Nevada
Context triple: [Mount Diablo meridian, jurisdiction, State of Nevada]
  • A. Nevada chosen
    Nevada is a western U.S. state known for its vast deserts, legalized gambling, and the entertainment hub of Las Vegas.
  • B. Arizona
    Arizona is a southwestern U.S. state known for its desert climate, the Grand Canyon, and major cities like Phoenix and Tucson.
  • C. southern Nevada
    Southern Nevada is the arid, heavily urbanized region of Nevada best known for encompassing the Las Vegas metropolitan area and its surrounding desert landscapes.
  • D. Utah
    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.
  • E. New Mexico
    New Mexico is a southwestern U.S. state known for its diverse landscapes, rich Native American and Hispanic cultural heritage, and historic cities like Santa Fe and Albuquerque.
  • 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_69a2e7951ba08190960e90823b5078f3 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2eb0019088190a9b969c4287dc4fa completed Feb. 28, 2026, 1:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac1cc7fc6c8190ac5da1e473396932 completed March 7, 2026, 12:40 p.m.
Created at: Feb. 28, 2026, 1:08 p.m.