Triple

T10617030
Position Surface form Disambiguated ID Type / Status
Subject Hector International Airport E276146 entity
Predicate state P87 FINISHED
Object North Dakota E31933 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: North Dakota | Statement: [Hector International Airport, state, North Dakota]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: North Dakota
Context triple: [Hector International Airport, state, North Dakota]
  • A. North Dakota chosen
    North Dakota is a sparsely populated U.S. state known for its Great Plains landscapes, agricultural economy, and significant oil production from the Bakken formation.
  • B. South Dakota
    South Dakota is a largely rural U.S. state known for the Black Hills, Mount Rushmore, and its Native American heritage.
  • C. Montana
    Montana is a large, sparsely populated U.S. state in the northern Rocky Mountains known for its expansive wilderness, national parks like Glacier, and wide-open "Big Sky" landscapes.
  • D. Montana
    Montana was a former Swiss alpine resort municipality that later became part of the larger resort area of Crans-Montana in the canton of Valais.
  • E. Nebraska
    Nebraska is a 2013 black-and-white American road comedy-drama film directed by Alexander Payne that follows an aging man's quixotic journey to claim a supposed sweepstakes prize.
  • 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_69d6aaf948d88190806cc3a8c47a3fb2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d6df6e2df4819099a19b59d90d0dd1 completed April 8, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69d9988fca088190b13b651985677a6a completed April 11, 2026, 12:40 a.m.
Created at: April 8, 2026, 7:33 p.m.