Triple

T1216393
Position Surface form Disambiguated ID Type / Status
Subject Central Florida E26115 entity
Predicate hasMajorCity P316 FINISHED
Object Lakeland 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 | Statement: [Central Florida, hasMajorCity, Lakeland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lakeland
Context triple: [Central Florida, hasMajorCity, Lakeland]
  • A. Lakeland
    Lakeland is a residential neighborhood located within the city of College Park in Prince George's County, Maryland.
  • B. 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.
  • C. Altamonte Springs
    Altamonte Springs is a suburban city in the Orlando metropolitan area of Central Florida, known for its residential communities, shopping centers, and recreational amenities.
  • 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. Bagdad, Florida
    Bagdad, Florida is a small unincorporated community and historic mill town located along the Blackwater River in the Florida Panhandle.
  • 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_69a4948331fc8190b531ac9bec71c491 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be059c5c8190a200f09442c22334 completed March 1, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad293648d08190a1c15fe677aa7b8c completed March 8, 2026, 7:45 a.m.
Created at: March 1, 2026, 7:46 p.m.