Triple

T11624111
Position Surface form Disambiguated ID Type / Status
Subject Principality of Hungary E276215 entity
Predicate notableRuler P22 FINISHED
Object Géza E513662 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: Géza | Statement: [Principality of Hungary, notableRuler, Géza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Géza
Context triple: [Principality of Hungary, notableRuler, Géza]
  • A. Géza chosen
    Géza was a 10th-century Grand Prince of the Hungarians who played a key role in consolidating the Hungarian state and paving the way for its Christianization under his son Stephen I.
  • B. György
    György is a Hungarian given name commonly used for men, equivalent to the English name George.
  • C. Béla
    Béla was a common medieval Hungarian royal given name borne by several kings, most notably Béla IV of Hungary.
  • D. Zoltán
    Zoltán was an early medieval Hungarian ruler, traditionally regarded as one of the first princes of the Principality of Hungary and a successor in the Árpád dynasty.
  • E. Jenő
    Jenő is the Hungarian given name of the renowned theoretical physicist and mathematician Wigner Jenő Pál, known in English as Eugene Wigner.
  • 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_69d6aafa51148190ab84940694c00235 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a122a3708190ab6513dad4c4fde7 completed April 10, 2026, 7:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef13491c0c819085f4ea17ad74612a completed April 27, 2026, 7:42 a.m.
Created at: April 8, 2026, 9:39 p.m.