Triple

T5616403
Position Surface form Disambiguated ID Type / Status
Subject Lakeland Linder International Airport E147487 entity
Predicate serves P98 FINISHED
Object Lakeland, Florida E155311 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: Lakeland, Florida | Statement: [Lakeland Linder International Airport, serves, Lakeland, Florida]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lakeland, Florida
Context triple: [Lakeland Linder International Airport, serves, Lakeland, Florida]
  • A. Lakeland, Florida chosen
    Lakeland, Florida is a mid-sized city in central Florida known for its numerous lakes, historic downtown, and long-standing ties to Major League Baseball.
  • B. Lakeland
    Lakeland is a residential neighborhood located within the city of College Park in Prince George's County, Maryland.
  • C. Lauderdale Lakes, Florida
    Lauderdale Lakes, Florida is a small suburban city in Broward County known for its diverse population and residential communities within the Miami metropolitan area.
  • D. Kissimmee, Florida
    Kissimmee, Florida is a central Florida city in Osceola County known for its proximity to major Orlando-area theme parks and tourist attractions.
  • E. Sarasota, Florida
    Sarasota, Florida is a Gulf Coast city known for its beaches, arts and cultural scene, and as a longtime hub for Major League Baseball spring training.
  • 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_69c00905d4588190bd967842bbcf2219 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c021da7f848190bb1cd0270ad6398f completed March 22, 2026, 5:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c107b36b3c819084d7e8fda4de74b7 completed March 23, 2026, 9:28 a.m.
Created at: March 22, 2026, 3:39 p.m.