Triple

T16709620
Position Surface form Disambiguated ID Type / Status
Subject HC Zlín E406068 entity
Predicate formerName P65 FINISHED
Object PSG Zlín E408793 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: PSG Zlín | Statement: [HC Zlín, formerName, PSG Zlín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PSG Zlín
Context triple: [HC Zlín, formerName, PSG Zlín]
  • A. PSG Zlín chosen
    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.
  • B. Dukla Pardubice
    Dukla Pardubice is a Czech sports club historically associated with the army-based Dukla sports association, known for competing in national-level competitions.
  • C. Dukla Brno
    Dukla Brno is a Czech sports club historically associated with the army-based Dukla sports association, best known for its achievements in cycling.
  • D. 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.
  • E. Dukla Liberec
    Dukla Liberec is a Czech sports club historically associated with the army sports association Dukla, known for competing at a high level in national competitions.
  • 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_69d8838db21081909589220fd71440a4 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3865186b48190bb45a761f5cf1a83 completed April 18, 2026, 1:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a51378788190b9f3bb0a344dcdd8 completed May 10, 2026, 3:32 p.m.
Created at: April 10, 2026, 5:20 a.m.