Triple

T15705760
Position Surface form Disambiguated ID Type / Status
Subject AS Trenčín E380704 entity
Predicate formerName P65 FINISHED
Object FK AS Trenčín E380704 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: FK AS Trenčín | Statement: [AS Trenčín, formerName, FK AS Trenčín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FK AS Trenčín
Context triple: [AS Trenčín, formerName, FK AS Trenčín]
  • A. HC Dukla Trenčín
    HC Dukla Trenčín is a professional ice hockey club from Trenčín, Slovakia, known for developing numerous NHL players including Zdeno Chára.
  • B. FC Spartak Trnava
    FC Spartak Trnava is a prominent Slovak football club known for its rich history, passionate fan base, and multiple national championship titles.
  • C. FK Dukla Banská Bystrica
    FK Dukla Banská Bystrica is a Slovak professional football club based in the city of Banská Bystrica, known for competing in the country’s top leagues.
  • D. football club AS Trenčín chosen
    AS Trenčín is a Slovak professional football club based in the city of Trenčín, known for competing in the country’s top league and developing young talent.
  • E. TJ Jednota Trenčín
    TJ Jednota Trenčín was a former name of the Slovak football club now known as AS Trenčín, which competes in the country’s top professional league.
  • 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_69d86d9bf930819082b30cf6d169297c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f6fc3608190a85b25755f5345db completed April 16, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82f05d648190a0c73b60dc027287 completed May 9, 2026, 6:54 p.m.
Created at: April 10, 2026, 4:45 a.m.