Triple

T3150884
Position Surface form Disambiguated ID Type / Status
Subject Orono, Maine E65873 entity
Predicate borders P224 FINISHED
Object Glenburn, Maine E332471 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: Glenburn, Maine | Statement: [Orono, Maine, borders, Glenburn, Maine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Glenburn, Maine
Context triple: [Orono, Maine, borders, Glenburn, Maine]
  • A. Glenburn, Maine chosen
    Glenburn, Maine is a small rural town in Penobscot County known for its residential character and proximity to the city of Bangor.
  • B. Greenbush, Maine
    Greenbush, Maine is a small rural town in Penobscot County known for its forested landscape and location along the Penobscot River in central Maine.
  • C. Brownfield, Maine
    Brownfield, Maine is a small rural town in western Maine known for its scenic landscapes, outdoor recreation, and proximity to the White Mountains.
  • D. Oakfield, Maine
    Oakfield, Maine is a small rural town located in Aroostook County in northern Maine, known for its forested landscape and outdoor recreation.
  • E. Mount Vernon, Maine
    Mount Vernon, Maine is a small rural town in central Maine known for its lakes, forests, and outdoor recreation, located within Kennebec County.
  • 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_69ad8584485081909ed529e890cadc4a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada5c145248190843ff3b1701074a1 completed March 8, 2026, 4:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf28e228608190a531da6024803e1b completed March 21, 2026, 11:25 p.m.
Created at: March 8, 2026, 3:05 p.m.