Triple

T14265461
Position Surface form Disambiguated ID Type / Status
Subject Stefan Mazurkiewicz E353631 entity
Predicate notableStudent P4838 FINISHED
Object Stanisław Saks E442716 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: Stanisław Saks | Statement: [Stefan Mazurkiewicz, notableStudent, Stanisław Saks]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stanisław Saks
Context triple: [Stefan Mazurkiewicz, notableStudent, Stanisław Saks]
  • A. Stanisław Saks chosen
    Stanisław Saks was a Polish mathematician known for his contributions to measure theory and real analysis and as a prominent member of the interwar Polish mathematical community.
  • B. Tadeusz Zaleski
    Tadeusz Zaleski is a Polish individual notable enough to be recognized as a prominent bearer of the surname Zaleski.
  • C. Aleksander Skrzyński
    Aleksander Skrzyński was a Polish diplomat and politician who served as Prime Minister of Poland in the interwar period.
  • D. Stanisław Kierbedź
    Stanisław Kierbedź was a 19th-century Polish engineer renowned for designing major bridges in the Russian Empire, including pioneering steel structures in Saint Petersburg.
  • E. Bolesław Sobociński
    Bolesław Sobociński was a Polish logician and philosopher known for his work in formal logic and as a prominent representative of the Lvov–Warsaw School.
  • 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6357a8188190ba518a486521052b completed April 14, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69fef883f2b88190807d9157e8d45e3c completed May 9, 2026, 9:04 a.m.
Created at: April 10, 2026, 1:09 a.m.