Triple

T1910291
Position Surface form Disambiguated ID Type / Status
Subject Bór E38092 entity
Predicate hasFamilyName P18 FINISHED
Object Komorowski E175219 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: Komorowski | Statement: [Bór, hasFamilyName, Komorowski]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Komorowski
Context triple: [Bór, hasFamilyName, Komorowski]
  • A. Edward Osóbka-Morawski
    Edward Osóbka-Morawski was a Polish socialist politician who served as one of the early post-World War II leaders of communist-dominated Poland, including as prime minister.
  • B. Zbigniew
    Zbigniew is a masculine Slavic given name, particularly common in Poland.
  • C. Jarosław Kaczyński
    Jarosław Kaczyński is a Polish politician and long-time leader of the conservative Law and Justice party, widely regarded as one of the most influential figures in contemporary Polish politics.
  • D. Bronisław Komorowski chosen
    Bronisław Komorowski is a Polish politician and historian who served as the country’s president from 2010 to 2015.
  • E. Zbigniew Wojna
    Zbigniew Wojna is a computer scientist and researcher known for his contributions to deep learning and computer vision, including coauthoring influential work with Christian Szegedy.
  • 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_69a8862a26088190aae5243695aeefc0 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb1b7095c8190ad7e472aada30d3d completed March 7, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeaffbc2c81908303548fac82ff52 completed March 8, 2026, 9:32 p.m.
Created at: March 4, 2026, 7:35 p.m.