Triple

T21037083
Position Surface form Disambiguated ID Type / Status
Subject Géza, Grand Prince of the Hungarians E518217 entity
Predicate title P38 FINISHED
Object Grand Prince 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: Grand Prince | Statement: [Géza, Grand Prince of the Hungarians, title, Grand Prince]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grand Prince
Context triple: [Géza, Grand Prince of the Hungarians, title, Grand Prince]
  • A. Grand Prince chosen
    Grand Prince was the medieval title held by the supreme ruler of the early Hungarian state before it became a Christian kingdom.
  • B. Fürst
    Fürst is a German noble title historically ranking below a duke and above a count, often translated as "prince" in English.
  • C. Prince of Verden
    The Prince of Verden was the secular ruler of the former Prince-Bishopric of Verden in the Holy Roman Empire, holding both territorial and noble authority over the region.
  • D. Prinze
    Prinze is the surname of American actor Freddie Prinze Jr., associated with a family of entertainers in film and television.
  • E. Prince Toneri
    Prince Toneri was an 8th-century Japanese imperial prince and scholar best known for overseeing the compilation of the historical chronicle Nihon Shoki.
  • 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_69e0b503275c8190afd9a163f997c709 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fcecf2508190a7647abb3c59debb completed April 21, 2026, 4:28 a.m.
Created at: April 16, 2026, 2:02 p.m.