Triple

T21068502
Position Surface form Disambiguated ID Type / Status
Subject Muskoka E519038 entity
Predicate containsLake P1025 FINISHED
Object Lake Rosseau 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: Lake Rosseau | Statement: [Muskoka, containsLake, Lake Rosseau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Rosseau
Context triple: [Muskoka, containsLake, Lake Rosseau]
  • A. Lake Rosseau chosen
    Lake Rosseau is a prominent recreational lake in Ontario’s Muskoka region, known for its upscale cottages, boating, and scenic natural surroundings.
  • B. Lake Cadillac
    Lake Cadillac is a popular inland lake in northwestern Michigan known for recreational activities such as boating, fishing, and lakeside tourism.
  • C. Lake Magog
    Lake Magog is a scenic alpine lake in British Columbia, Canada, renowned for its turquoise waters and dramatic views of Mount Assiniboine in the Canadian Rockies.
  • D. Lake King William
    Lake King William is an artificial reservoir in Tasmania, Australia, primarily used for hydroelectric power generation and water storage.
  • E. Lake Waban
    Lake Waban is a scenic freshwater lake in Wellesley, Massachusetts, known for its walking trails and its central role in the landscape of Wellesley College.
  • 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_69e0b505ef108190b25dd4033e2ff7eb completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6feb6d3a081909d6a6b181786deff completed April 21, 2026, 4:36 a.m.
Created at: April 16, 2026, 2:45 p.m.