Triple

T1148417
Position Surface form Disambiguated ID Type / Status
Subject Windsor International Airport E23619 entity
Predicate regionServed P82 FINISHED
Object Essex County E138819 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: Essex County | Statement: [Windsor International Airport, regionServed, Essex County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Essex County
Context triple: [Windsor International Airport, regionServed, Essex County]
  • A. Essex County
    Essex County is a historic coastal county in northeastern Massachusetts that includes cities such as Lynn, Salem, and Lawrence.
  • B. Essex County chosen
    Essex County is a southwestern Ontario region bordering Lake Erie that includes the southernmost point of mainland Canada and encompasses Point Pelee National Park.
  • C. Sussex County
    Sussex County is a county in the southern part of the U.S. state of Delaware, known for its coastal resorts, agriculture, and historic towns.
  • D. Middlesex County
    Middlesex County is a regional municipality in southwestern Ontario, Canada, that encompasses the city of London and several surrounding communities.
  • E. Middlesex County
    Middlesex County is a populous county in central New Jersey known for its diverse suburban communities, major transportation hubs, and proximity to New York City.
  • 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_69a493f0d32c8190ac74bad3c87f2641 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bc7190308190ab104480ed208b22 completed March 1, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac93b2283881908dde77abbbf864ae completed March 7, 2026, 9:08 p.m.
Created at: March 1, 2026, 7:44 p.m.