Triple

T15542677
Position Surface form Disambiguated ID Type / Status
Subject George Pomeroy Colley E370520 entity
Predicate familyName P18 FINISHED
Object Colley E744059 NE FINISHED

How this triple was built (2 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: Colley | Statement: [George Pomeroy Colley, familyName, Colley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colley
Context triple: [George Pomeroy Colley, familyName, Colley]
  • A. Colley chosen
    Colley is a surname most notably associated with American actor Don Pedro Colley, known for his roles in film and television during the 1960s–1980s.
  • B. De Colo
    De Colo is the surname of French professional basketball player Nando De Colo, known for his successful career in European leagues and international competitions.
  • C. Anson’s Colts
    Anson’s Colts was an early Major League Baseball team from Chicago in the late 19th century, managed and led by Hall of Famer Cap Anson.
  • D. Cooley
    Cooley was a party in the landmark 1852 U.S. Supreme Court case Cooley v. Board of Wardens, which helped define the scope of state versus federal power over commerce.
  • E. Cullum
    Cullum is a surname most notably associated with George Washington Cullum, a 19th-century American military engineer and superintendent of the United States Military Academy at West Point.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d85cc521a08190921fb50319dddc34 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04432c3808190bb5b653bf8de30c6 completed April 16, 2026, 2:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4558677881908704ac86c12e1fc4 completed May 9, 2026, 2:31 p.m.
Created at: April 10, 2026, 4:07 a.m.