Triple

T9332175
Position Surface form Disambiguated ID Type / Status
Subject Kennebunkport E224549 entity
Predicate county P75 FINISHED
Object York County E637984 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: York County | Statement: [Kennebunkport, county, York County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: York County
Context triple: [Kennebunkport, county, York County]
  • A. York County
    York County is a county in northern South Carolina that forms part of the greater Charlotte metropolitan region.
  • B. York County
    York County is a county in southeastern Virginia that forms part of the Hampton Roads metropolitan region along the Chesapeake Bay.
  • C. York County chosen
    York County is a coastal county in southwestern Maine known for its historic towns, beaches, and role as one of the state's earliest settled regions.
  • D. York County
    York County was a former county in Ontario, Canada, that historically encompassed the area around present-day Toronto before being restructured into regional municipalities.
  • E. Page County
    Page County is a rural county in southwestern Iowa known for its agricultural landscape and small communities.
  • 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_69ca8427a0c08190b749831d5ea98f02 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd37afceb88190ad7ffbc7b47a1caa completed April 1, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0e3c30ba88190b192621928136b87 completed April 4, 2026, 10:11 a.m.
Created at: March 30, 2026, 7:39 p.m.