Triple

T19286749
Position Surface form Disambiguated ID Type / Status
Subject Madawaska River E482332 entity
Predicate passesThrough P225 FINISHED
Object Calabogie 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: Calabogie | Statement: [Madawaska River, passesThrough, Calabogie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Calabogie
Context triple: [Madawaska River, passesThrough, Calabogie]
  • A. Calabogie chosen
    Calabogie is a small community in eastern Ontario, Canada, known for its lake, ski resort, and motorsports track.
  • B. Deseronto
    Deseronto is a small town in southeastern Ontario, Canada, located on the Bay of Quinte and known historically for its lumber and shipping industries.
  • C. Moosonee
    Moosonee is a remote northern Ontario community near James Bay, often considered a gateway to Canada’s Arctic region.
  • D. Nashwaak Valley
    Nashwaak Valley is a rural valley region in central New Brunswick, Canada, characterized by its forests, farms, and small communities along the Nashwaak River.
  • E. Sylvan Lake
    Sylvan Lake is a freshwater lake in northeastern Indiana known for recreation such as boating, fishing, and lakeside living.
  • 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_69d8e8cf61b0819096fe3e4107827c4e completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fc024a7081909a25d7cc4e048f79 completed April 20, 2026, 10:12 a.m.
Created at: April 10, 2026, 1:30 p.m.