Triple

T11792358
Position Surface form Disambiguated ID Type / Status
Subject Columbus Clippers E280418 entity
Predicate generalManager P537 FINISHED
Object Ken Schnacke E270716 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: Ken Schnacke | Statement: [Columbus Clippers, generalManager, Ken Schnacke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ken Schnacke
Context triple: [Columbus Clippers, generalManager, Ken Schnacke]
  • A. Ken Schnacke chosen
    Ken Schnacke is a longtime baseball executive best known for leading the Triple-A Columbus Clippers organization as its general manager.
  • B. Kevin Biegel
    Kevin Biegel is an American television writer and producer best known for co-creating the sitcom Cougar Town and working on shows like Scrubs and Enlisted.
  • C. Brian Snodgrass
    Brian Snodgrass is an individual notable enough to be recognized as a namesake of the surname Snodgrass.
  • D. Kevin Nolting
    Kevin Nolting is an American film editor best known for his work on Pixar animated features, including the Academy Award-winning film "Up."
  • E. Cliff Schmautz
    Cliff Schmautz was a Canadian professional ice hockey right winger best known for his prolific scoring in the Western Hockey League and later play in the NHL during the 1960s and 1970s.
  • 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_69d6ab258b808190b1735835c841e3a4 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a588d2c881909783c2d678c2a474 completed April 10, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6344d86648190ad270517b36c8815 completed May 2, 2026, 5:28 p.m.
Created at: April 8, 2026, 9:42 p.m.