Triple

T22727431
Position Surface form Disambiguated ID Type / Status
Subject John Abramovic E562032 entity
Predicate hasNameInLatinAlphabet P22444 FINISHED
Object John Abramovic 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: John Abramovic | Statement: [John Abramovic, hasNameInLatinAlphabet, John Abramovic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Abramovic
Context triple: [John Abramovic, hasNameInLatinAlphabet, John Abramovic]
  • A. John Abramovic chosen
    John Abramovic was an American professional basketball player best known for his time in the early Basketball Association of America, a precursor to the NBA.
  • B. Roman Abramovich
    Roman Abramovich is a Russian-Israeli billionaire businessman and investor best known for his long tenure as owner of the English football club Chelsea FC and his prominent role among Russia’s post-Soviet oligarchs.
  • C. Abramovich
    Abramovich is a Russian patronymic derived from the male given name Abram, indicating "son of Abram."
  • D. Aaron Abramovich
    Aaron Abramovich is one of the children of Russian-Israeli billionaire and former Chelsea F.C. owner Roman Abramovich.
  • E. Vladimir Markovic
    Vladimir Markovic is a prominent mathematician known for his influential work in geometric analysis and low-dimensional topology.
  • 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_69e24550859c81908727d91efc3a81b4 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1792a2ee48190bfbdde1a72adfd25 completed April 29, 2026, 3:21 a.m.
Created at: April 17, 2026, 3:20 p.m.