Triple

T10347941
Position Surface form Disambiguated ID Type / Status
Subject Sweden, Maine E243800 entity
Predicate borders P224 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: [Sweden, Maine, borders, Denmark, Maine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Denmark, Maine
Context triple: [Sweden, Maine, borders, 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e945d51881908dd2af6c78344c9b completed April 7, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d750879d308190893bd8425aaa49d7 completed April 9, 2026, 7:08 a.m.
Created at: April 6, 2026, 11:56 a.m.