Triple

T12355591
Position Surface form Disambiguated ID Type / Status
Subject Patten E294602 entity
Predicate hasToponymicUse P20238 FINISHED
Object Patten, Maine 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: Patten, Maine | Statement: [Patten, hasToponymicUse, Patten, Maine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Patten, Maine
Context triple: [Patten, hasToponymicUse, Patten, Maine]
  • A. Patten, Maine chosen
    Patten, Maine is a small rural town in Penobscot County known as a gateway to the Katahdin Woods and Waters National Monument and the North Maine Woods.
  • B. Burnham, Maine
    Burnham, Maine is a small rural town in central Maine known for its lakes, forests, and quiet residential character.
  • C. Lovell, Maine
    Lovell, Maine is a small rural town in Oxford County known for its scenic lakes and mountains in western Maine.
  • D. Shapleigh, Maine
    Shapleigh, Maine is a small rural town in southwestern Maine known for its forests, lakes, and outdoor recreation.
  • E. Newfield, Maine
    Newfield, Maine is a small rural town in southwestern Maine known for its forests, lakes, and historic village character.
  • 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_69d6ab6ccbec8190b09e2d357aa80064 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f8bc60c8190b0ceb84093e70db4 completed April 10, 2026, 6:20 p.m.
Created at: April 8, 2026, 9:54 p.m.