Triple

T13643057
Position Surface form Disambiguated ID Type / Status
Subject Oxford County E326033 entity
Predicate containsSettlement P847 FINISHED
Object Denmark, Maine E241984 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: Denmark, Maine | Statement: [Oxford County, containsSettlement, Denmark, Maine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Denmark, Maine
Context triple: [Oxford County, containsSettlement, Denmark, Maine]
  • A. Denmark, Maine chosen
    Denmark, Maine is a small rural town in Oxford County known for its lakeside setting in western Maine’s Lakes Region.
  • B. Norway, Maine
    Norway, Maine is a small New England town known for its historic downtown, lakes and outdoor recreation, located in western Maine.
  • C. Gray, Maine
    Gray, Maine is a small New England town in southern Maine known for its rural character, proximity to Portland, and the Maine Wildlife Park.
  • D. Sweden, Maine
    Sweden, Maine is a small rural town in Oxford County known for its scenic lakeside setting and outdoor recreation opportunities in western Maine.
  • E. Rockland, Maine
    Rockland, Maine is a coastal city in midcoast Maine known for its busy harbor, maritime industries, and role as a transportation and cultural hub for the region.
  • 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_69d8076beddc8190a53156f5bea77f5e completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc5ac2af88190976abe6606994eef completed April 12, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78af74a548190bc8bbe1a1410997a completed May 3, 2026, 5:50 p.m.
Created at: April 9, 2026, 9:51 p.m.