Triple

T12967796
Position Surface form Disambiguated ID Type / Status
Subject Ed Vargo E321310 entity
Predicate name P16 FINISHED
Object Ed Vargo E321310 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: Ed Vargo | Statement: [Ed Vargo, name, Ed Vargo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ed Vargo
Context triple: [Ed Vargo, name, Ed Vargo]
  • A. Ed Vargo chosen
    Ed Vargo was a prominent Major League Baseball umpire who worked in the National League for over two decades and officiated multiple World Series and All-Star Games.
  • B. Jim Veltman
    Jim Veltman is a former Canadian professional lacrosse player renowned as one of the greatest leaders and transition players in National Lacrosse League history, particularly with the Toronto Rock.
  • C. Phil DeVoss
    Phil DeVoss is a fictional character from the romantic comedy-drama film "Elizabethtown," which explores themes of family, failure, and self-discovery.
  • D. Jim Vallely
    Jim Vallely is an American television writer and producer best known for his work on acclaimed sitcoms such as "Arrested Development."
  • E. Jeff Vintar
    Jeff Vintar is an American screenwriter best known for his work on science fiction films, including co-writing the screenplay for the 2004 movie "I, Robot."
  • 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_69d80763bd6c819094437da5b20b01d2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e3f702481908f0f90f4f12d3f4d completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f71f0c11f88190b0f0fa1d0ec74a8d completed May 3, 2026, 10:10 a.m.
Created at: April 9, 2026, 8:31 p.m.