Triple

T8320884
Position Surface form Disambiguated ID Type / Status
Subject Gregor E194828 entity
Predicate hasPatronymicForm P7966 FINISHED
Object Gregorov E251633 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: Gregorov | Statement: [Gregor, hasPatronymicForm, Gregorov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gregorov
Context triple: [Gregor, hasPatronymicForm, Gregorov]
  • A. Grigor chosen
    Grigor is a given name, commonly used in various Eastern European and Caucasian cultures, that corresponds to the English name Gregory.
  • B. Grigori
    Grigori is the given name of Grigori Rasputin, the controversial Russian mystic and advisor to the Romanov royal family in the early 20th century.
  • C. Andrew Bogomil
    Andrew Bogomil is a disciplined and principled Beverly Hills Police Department lieutenant who becomes a key ally to Axel Foley in the Beverly Hills Cop film series.
  • D. Turchynov
    Turchynov is a Ukrainian politician and former acting president of Ukraine known for his roles in the country’s post-2014 political transition.
  • E. Gavril
    Gavril is a masculine given name, commonly used in Slavic and Eastern European cultures, that derives from the Hebrew name Gabriel.
  • 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_69ca82e7a8a88190a32bb5cc0feb012d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f67aee88190b245f8d6e57a40b2 completed March 31, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc6fee5dc8190b2de22d210884e51 completed April 2, 2026, 1:31 a.m.
Created at: March 30, 2026, 5:55 p.m.