Triple

T683635
Position Surface form Disambiguated ID Type / Status
Subject Miroslav Šatan E13234 entity
Predicate playedFor P2170 FINISHED
Object Dukla Trenčín E69719 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: Dukla Trenčín | Statement: [Miroslav Šatan, playedFor, Dukla Trenčín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dukla Trenčín
Context triple: [Miroslav Šatan, playedFor, Dukla Trenčín]
  • A. HC Dukla Trenčín chosen
    HC Dukla Trenčín is a professional ice hockey club from Trenčín, Slovakia, known for developing numerous NHL players including Zdeno Chára.
  • B. HC Slovan Bratislava
    HC Slovan Bratislava is a prominent professional ice hockey club from Bratislava, Slovakia, known as one of the country’s most successful and historically significant teams.
  • C. HC Lev Praha
    HC Lev Praha was a professional ice hockey club based in Prague, Czech Republic, that competed in the Kontinental Hockey League (KHL).
  • D. Trenčín
    Trenčín is a historic city in western Slovakia known for its medieval castle overlooking the Váh River and its role as a regional cultural and economic center.
  • E. Cracovia
    Cracovia is a historic Polish football club from Kraków, known as one of the oldest and most traditional teams in the country.
  • 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_69a4933e0f98819097d22766c49b61b8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a070d4c08190a510a8f9c1ae8076 completed March 1, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5dca153e081908facd835a79da25d completed March 2, 2026, 6:53 p.m.
Created at: March 1, 2026, 7:36 p.m.