Triple

T3510385
Position Surface form Disambiguated ID Type / Status
Subject Eagle Lake, Maine E74180 entity
Predicate locatedNear P294 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: [Eagle Lake, Maine, locatedNear, Fort Kent, Maine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fort Kent, Maine
Context triple: [Eagle Lake, Maine, locatedNear, 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc0e1f0c8190b054d9fba16ce4b3 completed March 8, 2026, 6:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4d3697848190be759069962a8f00 completed April 2, 2026, 11:04 a.m.
Created at: March 8, 2026, 3:19 p.m.