Triple

T3773996
Position Surface form Disambiguated ID Type / Status
Subject Ekstraklasa E83262 entity
Predicate hasClub P28155 FINISHED
Object Wisła Kraków E83027 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: Wisła Kraków | Statement: [Ekstraklasa, hasClub, Wisła Kraków]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wisła Kraków
Context triple: [Ekstraklasa, hasClub, Wisła Kraków]
  • A. Wisła Kraków chosen
    Wisła Kraków is one of Poland’s oldest and most successful football clubs, based in the city of Kraków.
  • B. Lech riverfront
    Lech riverfront is a scenic riverside area in Landsberg am Lech, Germany, known for its historic architecture, picturesque views, and popular walking paths along the River Lech.
  • C. Skawina
    Skawina is a town in southern Poland near Kraków, known for its industrial facilities and role as a local economic and transport hub.
  • D. Plac Krasińskich
    Plac Krasińskich is a historic square in Warsaw, Poland, known for its notable architecture and monuments commemorating Polish history, including the Warsaw Uprising.
  • E. Słupia
    Słupia is a river in northern Poland that flows through the Pomeranian region to the Baltic Sea.
  • 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_69ad8b235e608190b5a2b1d1bfcef50b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcc594c50819099ab5ac1b82f61a6 completed March 8, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4e52ebd988190b6e3a7d8069b74be completed March 14, 2026, 4:33 a.m.
Created at: March 8, 2026, 3:36 p.m.