Triple

T6860215
Position Surface form Disambiguated ID Type / Status
Subject Lara Antipova E158257 entity
Predicate hasFamilyName P18 FINISHED
Object Antipova E584549 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: Antipova | Statement: [Lara Antipova, hasFamilyName, Antipova]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Antipova
Context triple: [Lara Antipova, hasFamilyName, Antipova]
  • A. Zhdanova
    Zhdanova is a Russian-language surname commonly borne by women and associated with several notable figures in Russian and post-Soviet public life.
  • B. Khodchenkova
    Khodchenkova is the surname of Russian actress Svetlana Khodchenkova, known for her work in both Russian cinema and international films.
  • C. Ivanova
    Ivanova is a common Slavic surname, particularly prevalent in Russia and other Eastern European countries, typically indicating female lineage from someone named Ivan.
  • D. Galina
    Galina is a feminine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
  • E. Larisa Antipova chosen
    Larisa Antipova is a central female character in Boris Pasternak's novel "Doctor Zhivago," known for her complex romantic relationships and symbolic role amid the turmoil of the Russian Revolution.
  • 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_69c68830cdbc8190a8301c7a9d9f651a completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d8737fac81909fc546ca2bf6a278 completed March 27, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72fe79af081909baacbfd4d5e8f24 completed March 28, 2026, 1:33 a.m.
Created at: March 27, 2026, 2:21 p.m.