Triple

T19013415
Position Surface form Disambiguated ID Type / Status
Subject Michael I E465283 entity
Predicate father P120 FINISHED
Object Jeremi Wiśniowiecki NE NERFINISHED

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: Jeremi Wiśniowiecki | Statement: [Michael I, father, Jeremi Wiśniowiecki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeremi Wiśniowiecki
Context triple: [Michael I, father, Jeremi Wiśniowiecki]
  • A. Jeremi Wiśniowiecki chosen
    Jeremi Wiśniowiecki was a powerful 17th-century Polish-Lithuanian magnate and military leader known for his staunch defense of the Commonwealth’s eastern borderlands and his prominent role in suppressing Cossack uprisings.
  • B. Piotr Wysocki
    Piotr Wysocki was a Polish army officer and independence activist best known for initiating the November Uprising of 1830 against Russian rule.
  • C. Maciej Mielżyński
    Maciej Mielżyński was a Polish nobleman and military commander known for his prominent role in 19th-century Polish national uprisings against foreign rule.
  • D. Piotr Wojciechowski
    Piotr Wojciechowski is a Polish entrepreneur best known as a co-founder and leader of WB Electronics, a major defense and electronics company in Poland.
  • E. Piotr Wolski
    Piotr Wolski is a researcher known for co-authoring scientific work with machine learning scientist Marcin Andrychowicz.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dd025c188190a1d81f5b4ec7e2c6 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d6aac4dc8190ac51f22c13f1b96c completed April 20, 2026, 7:32 a.m.
Created at: April 10, 2026, 12:02 p.m.