Triple

T23449077
Position Surface form Disambiguated ID Type / Status
Subject Kęstutis Kemzūra E567723 entity
Predicate coachedTeam P2169 FINISHED
Object Asseco Prokom Gdynia NE NERFINISHED

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: Asseco Prokom Gdynia | Statement: [Kęstutis Kemzūra, coachedTeam, Asseco Prokom Gdynia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asseco Prokom Gdynia
Context triple: [Kęstutis Kemzūra, coachedTeam, Asseco Prokom Gdynia]
  • A. Asseco Gdynia chosen
    Asseco Gdynia is a Polish professional basketball club based in Gdynia, known for its success in domestic competitions and participation in European tournaments.
  • B. Comarch
    Comarch is a Polish multinational IT company specializing in software and services for telecommunications, finance, and enterprise management.
  • C. Asiatech
    Asiatech was a short-lived Formula One engine manufacturer that supplied customer engines in the early 2000s after acquiring Peugeot’s F1 engine program.
  • D. Skanska Poland
    Skanska Poland is the Polish branch of the global construction and development company Skanska, responsible for major infrastructure and building projects across Poland.
  • E. Sogeti
    Sogeti is a professional services and technology consulting company specializing in IT and engineering solutions, operating as a subsidiary of Capgemini.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2458b4c888190b1d7998f9862a558 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1a64b27988190b4722425da964407 completed April 29, 2026, 6:33 a.m.
Created at: April 17, 2026, 5:52 p.m.