Triple

T21112619
Position Surface form Disambiguated ID Type / Status
Subject Northeastern Nevada E520210 entity
Predicate contains P35 FINISHED
Object Lander County NE NERFINISHED

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: Lander County | Statement: [Northeastern Nevada, contains, Lander County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lander County
Context triple: [Northeastern Nevada, contains, Lander County]
  • A. Lander County chosen
    Lander County is a sparsely populated, rural county in north-central Nevada known for its mining history and wide expanses of high desert and mountain terrain.
  • B. Mineral County
    Mineral County is a rural county in western Nevada known for its mining history, desert landscapes, and the Hawthorne Army Depot.
  • C. Mineral County
    Mineral County is a sparsely populated, heavily forested county in western Montana known for its mountainous terrain, outdoor recreation, and proximity to the Idaho border.
  • D. Sheridan County
    Sheridan County is a rural county in northwestern Kansas known for its agricultural landscape and small communities such as Selden.
  • E. Treasure County
    Treasure County is a sparsely populated rural county in south-central Montana known for its agricultural landscape along the Yellowstone River.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b509a318819092fbbcb21d1fe603 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e72103b3888190a19e9a40f01fb439 completed April 21, 2026, 7:02 a.m.
Created at: April 16, 2026, 2:54 p.m.