Triple

T8524862
Position Surface form Disambiguated ID Type / Status
Subject Huber Heights, Ohio E201786 entity
Predicate namedAfter P63 FINISHED
Object Charles Huber
Charles Huber was a local developer and community figure after whom the city of Huber Heights, Ohio, was named.
 E751659 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: Charles Huber | Statement: [Huber Heights, Ohio, namedAfter, Charles Huber]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Charles Huber
Context triple: [Huber Heights, Ohio, namedAfter, Charles Huber]
  • A. Hubert Gessner
    Hubert Gessner was an Austrian architect known for his influential early 20th-century residential and public building designs, particularly in Vienna.
  • B. Johann Huber
    Johann Huber is a relatively common German-language personal name shared by several notable individuals across fields such as theology, politics, and academia.
  • C. Joseph Huber
    Joseph Huber is a German sociologist and economist known for his work on ecological modernization and monetary reform.
  • D. Charles Huet
    Charles Huet was an artist and mentor known primarily as the teacher of the French painter Jean-Baptiste Huet.
  • E. Karl Huber
    Karl Huber was a German politician who served as a high-ranking official in Nazi Germany’s interior administration.
  • 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: Charles Huber
Triple: [Huber Heights, Ohio, namedAfter, Charles Huber]
Generated description
Charles Huber was a local developer and community figure after whom the city of Huber Heights, Ohio, was named.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Charles Huber
Target entity description: Charles Huber was a local developer and community figure after whom the city of Huber Heights, Ohio, was named.
  • A. Hubert Gessner
    Hubert Gessner was an Austrian architect known for his influential early 20th-century residential and public building designs, particularly in Vienna.
  • B. Johann Huber
    Johann Huber is a relatively common German-language personal name shared by several notable individuals across fields such as theology, politics, and academia.
  • C. Joseph Huber
    Joseph Huber is a German sociologist and economist known for his work on ecological modernization and monetary reform.
  • D. Charles Huet
    Charles Huet was an artist and mentor known primarily as the teacher of the French painter Jean-Baptiste Huet.
  • E. Karl Huber
    Karl Huber was a German politician who served as a high-ranking official in Nazi Germany’s interior administration.
  • 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_69ca83228b24819085d22e7dc99f5d94 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe644c4648190a14dcaeaa90d72c7 completed March 31, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69cef30c02908190892234cab9a22ad4 completed April 2, 2026, 10:51 p.m.
NEDg Description generation batch_69cef4cbc0788190bf95aa8058a8d895 completed April 2, 2026, 10:59 p.m.
NED2 Entity disambiguation (via description) batch_69cef830e4e48190bf337a526cc82119 completed April 2, 2026, 11:13 p.m.
Created at: March 30, 2026, 6:16 p.m.