Triple

T3287707
Position Surface form Disambiguated ID Type / Status
Subject Dayton Callie E69022 entity
Predicate givenName P17 FINISHED
Object Dayton
Dayton is a masculine given name of English origin used both as a first name and a surname.
 E417952 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: Dayton | Statement: [Dayton Callie, givenName, Dayton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dayton
Context triple: [Dayton Callie, givenName, Dayton]
  • A. Dayton
    Dayton is an unincorporated community and census-designated place located within South Brunswick Township in Middlesex County, New Jersey.
  • B. Dayton
    Dayton is a mid-sized city in southwestern Ohio known for its historic role in aviation, manufacturing, and research, including its close association with major U.S. Air Force installations.
  • C. Dayton metropolitan area
    The Dayton metropolitan area is a regional urban and economic hub in southwestern Ohio centered on the city of Dayton and its surrounding communities.
  • D. Cincinnati
    Cincinnati is a major city in southwestern Ohio, known for its historic architecture, riverfront location on the Ohio River, and role as a regional economic and cultural center.
  • E. Akron
    Akron is an industrial city in northeastern Ohio known historically for its rubber and tire manufacturing industry.
  • 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: Dayton
Triple: [Dayton Callie, givenName, Dayton]
Generated description
Dayton is a masculine given name of English origin used both as a first name and a surname.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dayton
Target entity description: Dayton is a masculine given name of English origin used both as a first name and a surname.
  • A. Dayton
    Dayton is an unincorporated community and census-designated place located within South Brunswick Township in Middlesex County, New Jersey.
  • B. Dayton
    Dayton is a mid-sized city in southwestern Ohio known for its historic role in aviation, manufacturing, and research, including its close association with major U.S. Air Force installations.
  • C. Dayton metropolitan area
    The Dayton metropolitan area is a regional urban and economic hub in southwestern Ohio centered on the city of Dayton and its surrounding communities.
  • D. Cincinnati
    Cincinnati is a major city in southwestern Ohio, known for its historic architecture, riverfront location on the Ohio River, and role as a regional economic and cultural center.
  • E. Akron
    Akron is an industrial city in northeastern Ohio known historically for its rubber and tire manufacturing industry.
  • 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_69ad859d45748190b0742408c954b39f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb058e00881908fdf0a23208860d4 completed March 8, 2026, 5:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f070d6081909bc6ae1ce127c3d7 completed March 14, 2026, 3:30 p.m.
NEDg Description generation batch_69b582f9c858819094de05e240c98594 completed March 14, 2026, 3:47 p.m.
NED2 Entity disambiguation (via description) batch_69b5836543848190abbf31c04804358d completed March 14, 2026, 3:48 p.m.
Created at: March 8, 2026, 3:10 p.m.