Triple

T5691688
Position Surface form Disambiguated ID Type / Status
Subject Southwestern Ohio E125440 entity
Predicate hasCity P316 FINISHED
Object Wilmington, Ohio
Wilmington, Ohio is a small city in southwestern Ohio known historically as a regional transportation hub and home to a major air park and agricultural community.
E597370 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: Wilmington, Ohio | Statement: [Southwestern Ohio, hasCity, Wilmington, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wilmington, Ohio
Context triple: [Southwestern Ohio, hasCity, Wilmington, Ohio]
  • A. New London, Ohio
    New London, Ohio is a small village in Huron County known for its rural character and location in north-central Ohio.
  • B. Harrisburg, Ohio
    Harrisburg, Ohio is a small village in central Ohio that functions as part of the Columbus metropolitan area.
  • C. Fremont, Ohio
    Fremont, Ohio is a small city in northern Ohio best known as the longtime home and burial place of U.S. President Rutherford B. Hayes.
  • D. Newark, Ohio
    Newark, Ohio is a mid-sized city in central Ohio known as the county seat of Licking County and a regional hub for industry, education, and transportation.
  • E. Brunswick, Ohio
    Brunswick, Ohio is a suburban city in Medina County that forms part of the Greater Cleveland metropolitan area.
  • 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: Wilmington, Ohio
Triple: [Southwestern Ohio, hasCity, Wilmington, Ohio]
Generated description
Wilmington, Ohio is a small city in southwestern Ohio known historically as a regional transportation hub and home to a major air park and agricultural community.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Wilmington, Ohio
Target entity description: Wilmington, Ohio is a small city in southwestern Ohio known historically as a regional transportation hub and home to a major air park and agricultural community.
  • A. New London, Ohio
    New London, Ohio is a small village in Huron County known for its rural character and location in north-central Ohio.
  • B. Harrisburg, Ohio
    Harrisburg, Ohio is a small village in central Ohio that functions as part of the Columbus metropolitan area.
  • C. Fremont, Ohio
    Fremont, Ohio is a small city in northern Ohio best known as the longtime home and burial place of U.S. President Rutherford B. Hayes.
  • D. Newark, Ohio
    Newark, Ohio is a mid-sized city in central Ohio known as the county seat of Licking County and a regional hub for industry, education, and transportation.
  • E. Brunswick, Ohio
    Brunswick, Ohio is a suburban city in Medina County that forms part of the Greater Cleveland metropolitan area.
  • 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_69c0082bb19c8190823a4facd3cba79b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023e500ec8190bfda4f6a818aa5dc completed March 22, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c65fa576888190a3fd0fb3eac72a3f completed March 27, 2026, 10:44 a.m.
NEDg Description generation batch_69c66032e6dc8190a6e250750c9dc88f completed March 27, 2026, 10:47 a.m.
NED2 Entity disambiguation (via description) batch_69c660eb84b481909099ef2f473b296e completed March 27, 2026, 10:50 a.m.
Created at: March 22, 2026, 3:44 p.m.