Triple

T2811196
Position Surface form Disambiguated ID Type / Status
Subject MLS Cup 2013 E54173 entity
Predicate homeTeamCoach P5835 FINISHED
Object Peter Vermes E69347 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: Peter Vermes | Statement: [MLS Cup 2013, homeTeamCoach, Peter Vermes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Vermes
Context triple: [MLS Cup 2013, homeTeamCoach, Peter Vermes]
  • A. Peter Vermes chosen
    Peter Vermes is an American soccer coach and former defender best known for his long tenure leading Sporting Kansas City in Major League Soccer.
  • B. Sigi Schmid
    Sigi Schmid was a highly successful German-American soccer coach best known for leading MLS clubs like the LA Galaxy, Columbus Crew, and Seattle Sounders to multiple league titles and trophies.
  • C. Tom Nissalke
    Tom Nissalke was an American professional basketball coach best known for his work in the ABA and NBA during the 1970s and 1980s.
  • D. Pascal Jost
    Pascal Jost is a French local politician serving as the mayor of the commune of Veckring in northeastern France.
  • E. Wayne Tinkle
    Wayne Tinkle is an American college basketball coach best known for leading the Oregon State Beavers men's basketball program and previously revitalizing the University of Montana team.
  • 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_69ab49dcee188190b5c6eca9ae9e3469 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde354a5881908cd3d545f7dda81c completed March 7, 2026, 8:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69afce9a76388190a5dce756de2eb59f completed March 10, 2026, 7:56 a.m.
Created at: March 6, 2026, 9:59 p.m.