Triple

T19044216
Position Surface form Disambiguated ID Type / Status
Subject Mieszko II Lambert E466086 entity
Predicate successor P78 FINISHED
Object Bezprym 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: Bezprym | Statement: [Mieszko II Lambert, successor, Bezprym]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bezprym
Context triple: [Mieszko II Lambert, successor, Bezprym]
  • A. Bezprym chosen
    Bezprym was an early 11th-century Polish duke, briefly ruling as the ruler of Poland after deposing his half-brother Mieszko II before being overthrown and killed.
  • B. Niesky
    Niesky is a small town in eastern Saxony, Germany, known for its historical connections to regional conflicts and its location near the Polish border.
  • C. Bzura
    Bzura is a river in central Poland known for its historical significance, including being the site of a major World War II battle.
  • D. Oszmiana
    Oszmiana is a historic town in present-day Belarus that was once an important local center within the former Polish–Lithuanian Commonwealth.
  • E. Biegun
    Biegun is a Polish surname borne by various individuals, including figures in politics, academia, and the arts.
  • 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_69d8dd0359648190bc2a9202c5cf29d2 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d802a75c8190a4ce45e5fbffc1b7 completed April 20, 2026, 7:38 a.m.
Created at: April 10, 2026, 12:03 p.m.