Triple

T14934282
Position Surface form Disambiguated ID Type / Status
Subject George E372348 entity
Predicate hasVariant P455 FINISHED
Object György E411309 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: György | Statement: [George, hasVariant, György]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: György
Context triple: [George, hasVariant, György]
  • A. György chosen
    György is a Hungarian given name commonly used for men, equivalent to the English name George.
  • B. Ernő
    Ernő is a Hungarian-born British modernist architect best known for his influential and often controversial Brutalist buildings in London.
  • C. 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.
  • D. Lajos
    Lajos is a Hungarian masculine given name commonly used in Central and Eastern Europe.
  • E. Géza
    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.
  • 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_69d85cc9da0c81908d583ca3f63a3908 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded646a0808190ba5c0c91bde011c5 completed April 15, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69feef603b788190ad747d73af2363d4 completed May 9, 2026, 8:25 a.m.
Created at: April 10, 2026, 2:37 a.m.