Triple

T2664571
Position Surface form Disambiguated ID Type / Status
Subject John E55602 entity
Predicate hasVariant P455 FINISHED
Object Ivan E157814 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: Ivan | Statement: [John, hasVariant, Ivan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ivan
Context triple: [John, hasVariant, Ivan]
  • A. Ivan chosen
    Ivan is a common Slavic male given name widely used in Russia and other Eastern European countries, equivalent to "John" in English.
  • B. Vasily
    Vasily is a masculine given name of Slavic origin, commonly used in Russian-speaking countries.
  • C. Fyodor
    Fyodor is a masculine given name of Russian origin, most famously borne by the novelist Fyodor Dostoevsky.
  • D. Pyotr
    Pyotr is the Russian given name of Peter Kropotkin, the influential 19th-century anarchist philosopher, geographer, and revolutionary.
  • E. Viktor
    Viktor is a powerful and ancient vampire elder from the "Underworld" film series, portrayed by actor Bill Nighy.
  • 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_69ab49e54de48190be708cd1cf8be073 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd96dba44819085c3e651afba7806 completed March 7, 2026, 7:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5627344648190b2794d4e71524bf4 completed March 14, 2026, 1:28 p.m.
Created at: March 6, 2026, 9:54 p.m.