Triple

T10498532
Position Surface form Disambiguated ID Type / Status
Subject Oxford Casino Hotel E247606 entity
Predicate locatedIn P40 FINISHED
Object Oxford, Maine E49272 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: Oxford, Maine | Statement: [Oxford Casino Hotel, locatedIn, Oxford, Maine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oxford, Maine
Context triple: [Oxford Casino Hotel, locatedIn, Oxford, Maine]
  • A. Oxford, Maine chosen
    Oxford, Maine is a small town in Oxford County known for its rural character, outdoor recreation, and the Oxford Plains Speedway.
  • B. Cambridge, Maine
    Cambridge, Maine is a small rural town in central Maine known for its quiet, forested landscape and location within Somerset County.
  • C. Oakland, Maine
    Oakland, Maine is a small town in central Maine known for its lakeside setting, residential character, and proximity to the city of Waterville.
  • D. Fairfield, Maine
    Fairfield, Maine is a small town in Somerset County known for its rural character, proximity to the Kennebec River, and role as part of the greater Waterville area in central Maine.
  • E. Waterford, Maine
    Waterford, Maine is a small rural town in Oxford County known for its lakes, forests, and traditional New England village character.
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5098e45ec8190a02b981a06786909 completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec869957481909ea4fded01851b70 completed May 9, 2026, 5:38 a.m.
Created at: April 6, 2026, 12:25 p.m.