Triple

T10569860
Position Surface form Disambiguated ID Type / Status
Subject Portland metropolitan area E249448 entity
Predicate containsTown P847 FINISHED
Object Limington, Maine E526978 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: Limington, Maine | Statement: [Portland metropolitan area, containsTown, Limington, Maine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Limington, Maine
Context triple: [Portland metropolitan area, containsTown, Limington, Maine]
  • A. Limington, Maine chosen
    Limington, Maine is a small rural town in southwestern Maine known for its historic character and location within York County.
  • B. Shapleigh, Maine
    Shapleigh, Maine is a small rural town in southwestern Maine known for its forests, lakes, and outdoor recreation.
  • C. Eliot, Maine
    Eliot, Maine is a small New England town in southern Maine known for its rural character, historic charm, and location along the Piscataqua River near the New Hampshire border.
  • D. Searsmont, Maine
    Searsmont, Maine is a small rural town in Waldo County known for its forests, lakes, and traditional New England character.
  • E. Waterford, Maine
    Waterford, Maine is a small rural town in Oxford County known for its lakes, forests, and traditional New England village character.
  • 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_6a000ebbc67c8190bd930a2773edb5b2 completed May 10, 2026, 4:51 a.m.
Created at: April 6, 2026, 12:37 p.m.