Triple

T8344445
Position Surface form Disambiguated ID Type / Status
Subject Tavon Young E195999 entity
Predicate givenName P17 FINISHED
Object Tavon
Tavon is a masculine given name, often used in the United States and associated with several contemporary public figures and athletes.
 E728642 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: Tavon | Statement: [Tavon Young, givenName, Tavon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tavon
Context triple: [Tavon Young, givenName, Tavon]
  • A. Treveris
    Treveris is the historical city now known as Trier, one of the oldest cities in Germany and a major center of the Roman Empire in the region.
  • B. Tino
    Tino is the commonly used nickname of former Major League Baseball first baseman Tino Martinez, best known for his years with the New York Yankees in the late 1990s and early 2000s.
  • C. Rennahan
    Rennahan is a surname most notably associated with Ray Rennahan, an American cinematographer known for his pioneering work with Technicolor.
  • D. Tavros
    Tavros is a suburban municipality in the Athens urban area of Greece, known for its mixed residential and industrial character.
  • E. Vaughn
    Vaughn is a surname most prominently associated with English film director and producer Matthew Vaughn, known for stylish action and comic-book adaptations.
  • 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: Tavon
Triple: [Tavon Young, givenName, Tavon]
Generated description
Tavon is a masculine given name, often used in the United States and associated with several contemporary public figures and athletes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tavon
Target entity description: Tavon is a masculine given name, often used in the United States and associated with several contemporary public figures and athletes.
  • A. Treveris
    Treveris is the historical city now known as Trier, one of the oldest cities in Germany and a major center of the Roman Empire in the region.
  • B. Tino
    Tino is the commonly used nickname of former Major League Baseball first baseman Tino Martinez, best known for his years with the New York Yankees in the late 1990s and early 2000s.
  • C. Rennahan
    Rennahan is a surname most notably associated with Ray Rennahan, an American cinematographer known for his pioneering work with Technicolor.
  • D. Tavros
    Tavros is a suburban municipality in the Athens urban area of Greece, known for its mixed residential and industrial character.
  • E. Vaughn
    Vaughn is a surname most prominently associated with English film director and producer Matthew Vaughn, known for stylish action and comic-book adaptations.
  • 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_69ca82edd63c8190b876b8465464c5fa completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fed6b588190ba5593859c8effc2 completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc733f7848190ab60098cb178dbfc completed April 2, 2026, 1:32 a.m.
NEDg Description generation batch_69cdcc8596888190867bb0f298b6fac1 completed April 2, 2026, 1:55 a.m.
NED2 Entity disambiguation (via description) batch_69cdd14de9408190a5522fbdbef4d748 completed April 2, 2026, 2:15 a.m.
Created at: March 30, 2026, 5:58 p.m.