Triple

T7451886
Position Surface form Disambiguated ID Type / Status
Subject Tommy Tuberville E172026 entity
Predicate familyName P18 FINISHED
Object Tuberville
Tuberville is the surname of Tommy Tuberville, an American politician and former college football coach.
 E665648 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: Tuberville | Statement: [Tommy Tuberville, familyName, Tuberville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tuberville
Context triple: [Tommy Tuberville, familyName, Tuberville]
  • A. Talmadge
    Talmadge is an American surname notably associated with several political and public figures, including members of the Talmadge family in Georgia.
  • B. Colemore
    Colemore is a small rural village and civil parish in East Hampshire, England, known for its historic church and agricultural surroundings.
  • C. Calhoun
    Calhoun is a small city in northwest Georgia known for its location along Interstate 75 and its role as a commercial and historical hub of Gordon County.
  • D. Kallahan
    Kallahan is an alternative name for the Kalanguya language, an Austronesian language spoken by indigenous communities in the northern Philippines.
  • E. Lumpkin
    Lumpkin is a surname of English origin borne by various notable individuals and families.
  • 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: Tuberville
Triple: [Tommy Tuberville, familyName, Tuberville]
Generated description
Tuberville is the surname of Tommy Tuberville, an American politician and former college football coach.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tuberville
Target entity description: Tuberville is the surname of Tommy Tuberville, an American politician and former college football coach.
  • A. Talmadge
    Talmadge is an American surname notably associated with several political and public figures, including members of the Talmadge family in Georgia.
  • B. Colemore
    Colemore is a small rural village and civil parish in East Hampshire, England, known for its historic church and agricultural surroundings.
  • C. Calhoun
    Calhoun is a small city in northwest Georgia known for its location along Interstate 75 and its role as a commercial and historical hub of Gordon County.
  • D. Kallahan
    Kallahan is an alternative name for the Kalanguya language, an Austronesian language spoken by indigenous communities in the northern Philippines.
  • E. Lumpkin
    Lumpkin is a surname of English origin borne by various notable individuals and families.
  • 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_69c68a66554c8190add75c65942c0317 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f38d6a8c8190af2e73c719da87a6 completed March 27, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c827b9a6048190bd3e3594b9cff2b7 completed March 28, 2026, 7:10 p.m.
NEDg Description generation batch_69c828e1487081908de825d60ea38c9e completed March 28, 2026, 7:15 p.m.
NED2 Entity disambiguation (via description) batch_69c829d8a15c8190911e0d7bda39c280 completed March 28, 2026, 7:19 p.m.
Created at: March 27, 2026, 3:14 p.m.