Triple

T8455689
Position Surface form Disambiguated ID Type / Status
Subject UMFK E199913 entity
Predicate locatedIn P40 FINISHED
Object Fort Kent, Maine E6034 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: Fort Kent, Maine | Statement: [UMFK, locatedIn, Fort Kent, Maine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fort Kent, Maine
Context triple: [UMFK, locatedIn, Fort Kent, Maine]
  • A. Fort Kent, Maine chosen
    Fort Kent, Maine is a small town in northern Aroostook County known for its location at the Canadian border and as a gateway to the North Maine Woods.
  • B. Mapleton, Maine
    Mapleton, Maine is a small rural town in northern Maine known for its agricultural landscape and location within Aroostook County.
  • C. Stetson, Maine
    Stetson, Maine is a small rural town in central Maine known for its lakes, forests, and quiet residential character.
  • D. Buxton, Maine
    Buxton, Maine is a small New England town in York County known for its rural character and proximity to the Portland metropolitan area.
  • E. Pownal, Maine
    Pownal, Maine is a small rural town in southern Maine known for its scenic landscapes and proximity to the Portland metropolitan area.
  • 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_69ca8318231881908fd1bc1c4d45d286 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe48e0ae481908b40f7f124b0551e completed March 31, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69cecc3c0d508190bc0c7bd89f040967 completed April 2, 2026, 8:06 p.m.
Created at: March 30, 2026, 6:10 p.m.