Triple

T671010
Position Surface form Disambiguated ID Type / Status
Subject National Academy of Public Administration E12970 entity
Predicate shortName P43 FINISHED
Object NAPA E12970 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: NAPA | Statement: [National Academy of Public Administration, shortName, NAPA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: NAPA
Context triple: [National Academy of Public Administration, shortName, NAPA]
  • A. NAPA chosen
    NAPA is a congressionally chartered, non-partisan organization that provides expert advice and analysis to improve government management and public administration in the United States.
  • B. Downey
    Downey is the surname of American actor Robert Downey Jr., widely known for his versatile film career and iconic role as Iron Man in the Marvel Cinematic Universe.
  • C. Riverside
    Riverside is a major inland city in Southern California known as the birthplace of the California citrus industry and a key center of the Inland Empire region.
  • D. Vallejo
    Vallejo is a waterfront city in the San Francisco Bay Area known for its former Mare Island Naval Shipyard and diverse, working-class community.
  • E. Henderson
    Henderson is a major city in the Las Vegas metropolitan area known for its rapid growth, residential communities, and proximity to the Las Vegas Strip.
  • 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_69a493355dec819098d4244b2fa34885 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49ffd2b508190ac5adc04163e360f completed March 1, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5c39f3e1481908f395cdb19cfd2fc completed March 2, 2026, 5:06 p.m.
Created at: March 1, 2026, 7:36 p.m.