Triple

T2045409
Position Surface form Disambiguated ID Type / Status
Subject Paris, Maine E45438 entity
Predicate adjacentTo P224 FINISHED
Object Norway, Maine E47275 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: Norway, Maine | Statement: [Paris, Maine, adjacentTo, Norway, Maine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norway, Maine
Context triple: [Paris, Maine, adjacentTo, Norway, Maine]
  • A. Norway, Maine chosen
    Norway, Maine is a small New England town known for its historic downtown, lakes and outdoor recreation, located in western Maine.
  • B. Caribou, Maine
    Caribou, Maine is a small city in northern Maine known for its agricultural economy, especially potato farming, and its proximity to outdoor recreation in Aroostook County.
  • C. Westmanland, Maine
    Westmanland, Maine is a small rural town located in northern Maine within Aroostook County.
  • D. Madawaska, Maine
    Madawaska, Maine is a small town in far northern Maine on the Canadian border, known for its Franco-American heritage and position as one of the four geographic corners of the United States.
  • E. Lebanon, Maine
    Lebanon, Maine is a small rural town in southwestern Maine known for its forests, lakes, and proximity to the New Hampshire border.
  • 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_69a8891948208190ab7898da21824c77 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9728f688190939d7c4df524f9b4 completed March 7, 2026, 5:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69b38b9e52688190bd9dc7fb17e892f8 completed March 13, 2026, 3:59 a.m.
Created at: March 4, 2026, 7:39 p.m.