Triple

T4566980
Position Surface form Disambiguated ID Type / Status
Subject Miner E121932 entity
Predicate hasNotableBearer P458 FINISHED
Object Alonzo Miner
Alonzo Miner was a 19th-century American Universalist clergyman, educator, and temperance advocate who served as president of Tufts College.
E453427 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: Alonzo Miner | Statement: [Miner, hasNotableBearer, Alonzo Miner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alonzo Miner
Context triple: [Miner, hasNotableBearer, Alonzo Miner]
  • A. Alonzo Harris
    Alonzo Harris is a corrupt and manipulative LAPD narcotics detective portrayed by Denzel Washington in the film "Training Day."
  • B. Charles Alverson
    Charles Alverson was an American writer and editor best known for his work in speculative fiction and his collaborations with Terry Gilliam on film projects.
  • C. Lawrence Payton
    Lawrence Payton was an American singer, songwriter, and arranger best known as a founding member of the Motown vocal group the Four Tops.
  • D. Rasual Butler
    Rasual Butler was an American professional basketball player and sharpshooting wing who played over a decade in the NBA for multiple teams.
  • E. Victor Milner
    Victor Milner was an American cinematographer and Academy Award winner known for his work on numerous classic Hollywood films during the early to mid-20th century.
  • 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: Alonzo Miner
Triple: [Miner, hasNotableBearer, Alonzo Miner]
Generated description
Alonzo Miner was a 19th-century American Universalist clergyman, educator, and temperance advocate who served as president of Tufts College.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Alonzo Miner
Target entity description: Alonzo Miner was a 19th-century American Universalist clergyman, educator, and temperance advocate who served as president of Tufts College.
  • A. Alonzo Harris
    Alonzo Harris is a corrupt and manipulative LAPD narcotics detective portrayed by Denzel Washington in the film "Training Day."
  • B. Charles Alverson
    Charles Alverson was an American writer and editor best known for his work in speculative fiction and his collaborations with Terry Gilliam on film projects.
  • C. Lawrence Payton
    Lawrence Payton was an American singer, songwriter, and arranger best known as a founding member of the Motown vocal group the Four Tops.
  • D. Rasual Butler
    Rasual Butler was an American professional basketball player and sharpshooting wing who played over a decade in the NBA for multiple teams.
  • E. Victor Milner
    Victor Milner was an American cinematographer and Academy Award winner known for his work on numerous classic Hollywood films during the early to mid-20th century.
  • 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_69bd463f156881908a99aca69c5721ac completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd589e35808190aa609bb04b128dbe completed March 20, 2026, 2:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdd3b560a08190a485e9ec45e0f0f8 completed March 20, 2026, 11:09 p.m.
NEDg Description generation batch_69bdd467cd0c8190a92938a69211f558 completed March 20, 2026, 11:12 p.m.
NED2 Entity disambiguation (via description) batch_69bdd4c432dc81909911de3d2943e3d5 completed March 20, 2026, 11:14 p.m.
Created at: March 20, 2026, 1:09 p.m.