Triple

T2318649
Position Surface form Disambiguated ID Type / Status
Subject Hampden, Maine E51123 entity
Predicate adjacentTo P224 FINISHED
Object Carmel, Maine E326187 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: Carmel, Maine | Statement: [Hampden, Maine, adjacentTo, Carmel, Maine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carmel, Maine
Context triple: [Hampden, Maine, adjacentTo, Carmel, Maine]
  • A. Carmel, Maine chosen
    Carmel, Maine is a small rural town in Penobscot County known for its close-knit community and proximity to the Bangor metropolitan area.
  • B. Waterford, Maine
    Waterford, Maine is a small rural town in Oxford County known for its lakes, forests, and traditional New England village character.
  • C. Merrill, Maine
    Merrill, Maine is a small rural town located in Aroostook County in the northern part of the U.S. state of Maine.
  • D. Sanford, Maine
    Sanford, Maine is a city in York County known for its historic textile mill heritage and its location in southern Maine near the New Hampshire border.
  • E. Lovell, Maine
    Lovell, Maine is a small rural town in Oxford County known for its scenic lakes and mountains in western Maine.
  • 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_69a88b074b908190ae983dbca7757d88 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc62fa60c8190b4859ce296ea4177 completed March 7, 2026, 6:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69c6d4f458288190ac1d6a8489bbc943 completed March 27, 2026, 7:05 p.m.
Created at: March 4, 2026, 7:49 p.m.