Triple

T10755859
Position Surface form Disambiguated ID Type / Status
Subject KLGC E253691 entity
Predicate subjectAirportServes P51581 FINISHED
Object LaGrange metropolitan area E30624 NE FINISHED

How this triple was built (3 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: LaGrange metropolitan area | Statement: [KLGC, subjectAirportServes, LaGrange metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LaGrange metropolitan area
Context triple: [KLGC, subjectAirportServes, LaGrange metropolitan area]
  • A. LaGrange
    LaGrange is a town in Dutchess County, New York, known as a suburban community in the Hudson Valley region.
  • B. LaGrange chosen
    LaGrange is a small city in western Georgia known for its historic downtown, proximity to West Point Lake, and role as an economic and cultural center for the surrounding region.
  • C. LaGrange
    LaGrange is a small village in northeastern Ohio, United States, known for its residential community and local parks.
  • D. Macon metropolitan area
    The Macon metropolitan area is a regional urban and economic hub in central Georgia centered on the city of Macon and its surrounding communities.
  • E. Savannah metropolitan area
    The Savannah metropolitan area is a coastal urban region in southeastern Georgia centered on the historic port city of Savannah, known for its tourism, logistics, and cultural heritage.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: subjectAirportServes
Context triple: [KLGC, subjectAirportServes, LaGrange metropolitan area]
  • A. airportServesAs
    Indicates that an airport functions in a particular role or capacity (such as primary, secondary, or hub) for a specified area, organization, or service.
  • B. associatedAirportServes chosen
    Indicates that a given airport provides service to, or is used by, the associated entity (such as a city, region, or facility).
  • C. airportServed
    Indicates that a particular airport provides service to, or is used for air travel to and from, a given location or area.
  • D. servesAirport
    Indicates that a transportation service or route provides access to and operates for a particular airport.
  • E. usesAirportCode
    Indicates that one entity employs or identifies an airport by a specific standardized airport code.
  • F. None of above.

Provenance (4 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_69d6aa5f54f4819082d0bbcb6f8797e6 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d72e9e224c819099d16aba77322812 completed April 9, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69dff78257b88190942308719d9fa6a6 completed April 15, 2026, 8:39 p.m.
PD Predicate disambiguation batch_69d6f311529c819080ca5493d55d6050 completed April 9, 2026, 12:30 a.m.
Created at: April 8, 2026, 9:15 p.m.