Triple

T434037
Position Surface form Disambiguated ID Type / Status
Subject Penobscot County, Maine E9773 entity
Predicate hasTown P847 FINISHED
Object Etna, Maine E17123 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: Etna, Maine | Statement: [Penobscot County, Maine, hasTown, Etna, Maine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Etna, Maine
Context triple: [Penobscot County, Maine, hasTown, Etna, Maine]
  • A. Etna, Maine chosen
    Etna, Maine is a small rural town in Penobscot County known for its quiet residential character and location along major east–west travel routes in central Maine.
  • B. Hermon, Maine
    Hermon, Maine is a small town in Penobscot County known as a suburban community of Bangor with a mix of rural character and growing residential development.
  • C. Palmyra, Maine
    Palmyra, Maine is a small rural town in Somerset County known for its location along major transportation routes in central Maine.
  • D. Rangeley, Maine
    Rangeley, Maine is a small resort town in western Maine known for its lakes, outdoor recreation, and scenic mountain surroundings.
  • E. Brownfield, Maine
    Brownfield, Maine is a small rural town in western Maine known for its scenic landscapes, outdoor recreation, and proximity to the White Mountains.
  • 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_69a2e801e1d48190b505d1dd336b52ac completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ef0a008c8190ae0aa25e4df9c35f completed Feb. 28, 2026, 1:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69a6373911408190adfe7fc909c93658 completed March 3, 2026, 1:19 a.m.
Created at: Feb. 28, 2026, 1:11 p.m.