Triple

T18235884
Position Surface form Disambiguated ID Type / Status
Subject Town of Bowmanville E436672 entity
Predicate hasNeighbouringCommunity P4647 FINISHED
Object Orono 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: Orono | Statement: [Town of Bowmanville, hasNeighbouringCommunity, Orono]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orono
Context triple: [Town of Bowmanville, hasNeighbouringCommunity, Orono]
  • A. Orono
    Orono is a suburban city in Minnesota known for its affluent residential communities and scenic location along the north shore of Lake Minnetonka.
  • B. Orono chosen
    Orono is a small rural village in Ontario, Canada, known for its historic downtown, agricultural surroundings, and community events.
  • C. Orono, Maine
    Orono, Maine is a small town in Penobscot County best known as the home of the University of Maine’s flagship campus.
  • D. Gardiner
    Gardiner is an English surname historically associated with Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • E. Gardiner
    Gardiner is a commonly used short name for the Gardiner Expressway, a major elevated highway running along Toronto’s waterfront.
  • 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_69d8b91104e08190a8241f7d260a5162 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4f4b69a688190b140961eb298c36e completed April 19, 2026, 3:28 p.m.
Created at: April 10, 2026, 10:33 a.m.