Triple

T10569858
Position Surface form Disambiguated ID Type / Status
Subject Portland metropolitan area E249448 entity
Predicate containsTown P847 FINISHED
Object Dayton, Maine E527164 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: Dayton, Maine | Statement: [Portland metropolitan area, containsTown, Dayton, Maine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dayton, Maine
Context triple: [Portland metropolitan area, containsTown, Dayton, Maine]
  • A. Dayton, Maine chosen
    Dayton, Maine is a small rural town in southern Maine known for its quiet residential character and location along the Saco River in York County.
  • B. Dresden, Maine
    Dresden, Maine is a small rural town in Lincoln County known for its historic character and scenic location along the Kennebec River.
  • C. Durham, Maine
    Durham, Maine is a small rural town in southern Maine known for its quiet residential character and proximity to the Lewiston–Auburn and Portland metropolitan areas.
  • D. Frankfort, Maine
    Frankfort, Maine is a small rural town in Waldo County known for its scenic setting along the Penobscot River and its historic New England character.
  • E. Trenton, Maine
    Trenton, Maine is a small coastal town in Hancock County that serves as a gateway to Mount Desert Island and Acadia National Park.
  • 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_69d381c8bd708190acf3d275c908251e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d52730fd4481908b3f4eb80ca209f2 completed April 7, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69de550705788190bd35b9763b44f546 completed April 14, 2026, 2:53 p.m.
Created at: April 6, 2026, 12:37 p.m.