Triple

T13783924
Position Surface form Disambiguated ID Type / Status
Subject Penobscot Valley E331204 entity
Predicate hasTown P847 FINISHED
Object Orono E65873 NE FINISHED

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: [Penobscot Valley, hasTown, Orono]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orono
Context triple: [Penobscot Valley, hasTown, 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
    Orono is a small rural village in Ontario, Canada, known for its historic downtown, agricultural surroundings, and community events.
  • C. Orono, Maine chosen
    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 (3 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_69d81c58feb08190a77bca8bf7d6d20f completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0247ccc881908dad7b547221f15d completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00077201c08190a0c3bb259856d5c9 completed May 10, 2026, 4:20 a.m.
Created at: April 9, 2026, 10:11 p.m.