Triple

T17828072
Position Surface form Disambiguated ID Type / Status
Subject Waterton River E445174 entity
Predicate flowsThrough P225 FINISHED
Object Cardston 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: Cardston County | Statement: [Waterton River, flowsThrough, Cardston County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cardston County
Context triple: [Waterton River, flowsThrough, Cardston County]
  • A. Cardston County chosen
    Cardston County is a municipal district in southern Alberta, Canada, known for its rural communities, agriculture, and proximity to the Canada–United States border.
  • B. Baingoin County
    Baingoin County is a high-altitude administrative county in the Tibet Autonomous Region of China, known for its vast grasslands and pastoral economy.
  • C. Terry County
    Terry County is a rural county in western Texas known for its agriculture, particularly cotton farming, and its location on the South Plains region.
  • D. Wheatland County
    Wheatland County is a rural municipal district in southern Alberta, Canada, located east of Calgary and known for its agricultural lands and small communities.
  • E. Windeyer County
    Windeyer County is a cadastral division in New South Wales, Australia, used for land administration and property title purposes.
  • 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_69d8b9f1a6d881909f024bc603111cdb completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48915d0fc819080ab03feb2465834 completed April 19, 2026, 7:49 a.m.
Created at: April 10, 2026, 10:15 a.m.