Triple

T1216397
Position Surface form Disambiguated ID Type / Status
Subject Central Florida E26115 entity
Predicate hasMajorCity P316 FINISHED
Object Clermont
Clermont is a rapidly growing city in Central Florida known for its rolling hills, lakes, and proximity to the greater Orlando metropolitan area.
 E139830 NE FINISHED

How this triple was built (4 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: Clermont | Statement: [Central Florida, hasMajorCity, Clermont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Clermont
Context triple: [Central Florida, hasMajorCity, Clermont]
  • A. Hillsborough
    Hillsborough is a historic football stadium in Sheffield, England, best known as the long-time home of Sheffield Wednesday F.C.
  • B. Belmont
    Belmont is a suburban district within the London Borough of Harrow, known for its residential character and local shopping and community facilities.
  • C. Belmont
    Belmont is a residential neighborhood in West Philadelphia known for its historic rowhouses and proximity to Fairmount Park.
  • D. Belmont
    Belmont is a suburban town in Middlesex County, Massachusetts, known for its residential character and proximity to Boston.
  • E. Belmont
    Belmont is a predominantly residential neighborhood in the central Bronx, New York City, historically known as the borough’s “Little Italy” for its Italian-American community and businesses.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Clermont
Triple: [Central Florida, hasMajorCity, Clermont]
Generated description
Clermont is a rapidly growing city in Central Florida known for its rolling hills, lakes, and proximity to the greater Orlando metropolitan area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Clermont
Target entity description: Clermont is a rapidly growing city in Central Florida known for its rolling hills, lakes, and proximity to the greater Orlando metropolitan area.
  • A. Hillsborough
    Hillsborough is a historic football stadium in Sheffield, England, best known as the long-time home of Sheffield Wednesday F.C.
  • B. Belmont
    Belmont is a suburban district within the London Borough of Harrow, known for its residential character and local shopping and community facilities.
  • C. Belmont
    Belmont is a residential neighborhood in West Philadelphia known for its historic rowhouses and proximity to Fairmount Park.
  • D. Belmont
    Belmont is a suburban town in Middlesex County, Massachusetts, known for its residential character and proximity to Boston.
  • E. Belmont
    Belmont is a predominantly residential neighborhood in the central Bronx, New York City, historically known as the borough’s “Little Italy” for its Italian-American community and businesses.
  • F. None of above. chosen

Provenance (5 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_69ac831fb6bc8190907f36e52489ec5c completed March 7, 2026, 7:57 p.m.
NEDg Description generation batch_69ac838fc3d08190aa43d7f2767fe7d2 completed March 7, 2026, 7:59 p.m.
NED2 Entity disambiguation (via description) batch_69ac8425ab408190a25c0f5db40ae77f completed March 7, 2026, 8:01 p.m.
Created at: March 1, 2026, 7:46 p.m.