Triple

T12162904
Position Surface form Disambiguated ID Type / Status
Subject Vitezslav Lavicka E289751 entity
Predicate managedClub P3239 FINISHED
Object Slovan Liberec E462549 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: Slovan Liberec | Statement: [Vitezslav Lavicka, managedClub, Slovan Liberec]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Slovan Liberec
Context triple: [Vitezslav Lavicka, managedClub, Slovan Liberec]
  • A. FC Slovan Liberec chosen
    FC Slovan Liberec is a Czech professional football club from the city of Liberec, known for competing in the country’s top league and winning multiple national championships.
  • B. Dukla Prague
    Dukla Prague is a historic Czech football club from Prague known for its success in the mid-20th century and for producing notable players such as Pavel Nedvěd.
  • C. FC Baník Ostrava
    FC Baník Ostrava is a professional Czech football club based in Ostrava, known for its passionate fan base and history in the country’s top league.
  • D. HC Škoda Plzeň
    HC Škoda Plzeň is a professional Czech ice hockey club based in Plzeň that competes in the country’s top-tier league.
  • E. PSG Zlín
    PSG Zlín is a Czech professional ice hockey club based in Zlín that competes in the country’s top leagues and has produced several notable players.
  • 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_69d6ab4d6c00819095a9a7c35de83cfb completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915c498a081908389598d0c247505 completed April 10, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a837a5881908c600be0be334269 completed May 2, 2026, 2:30 p.m.
Created at: April 8, 2026, 9:50 p.m.