Triple

T17595421
Position Surface form Disambiguated ID Type / Status
Subject La sconosciuta E428556 entity
Predicate stars P1956 FINISHED
Object Kseniya Rappoport 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: Kseniya Rappoport | Statement: [La sconosciuta, stars, Kseniya Rappoport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kseniya Rappoport
Context triple: [La sconosciuta, stars, Kseniya Rappoport]
  • A. Ksenia Rappoport chosen
    Ksenia Rappoport is a Russian actress acclaimed for her work in both Russian and Italian cinema, including award-winning performances in dramatic roles.
  • B. Rufina Gurevich
    Rufina Gurevich is a mathematician known for her work in areas influenced by Lev Pontryagin’s contributions to topology and control theory.
  • C. Tatiana Groshkova
    Tatiana Groshkova is a former Soviet artistic gymnast known for her powerful tumbling and contributions to the dominant Soviet women’s gymnastics program in the late 1980s.
  • D. Vera Kostrovitskaya
    Vera Kostrovitskaya was a prominent Russian ballet dancer and teacher associated with the classical St. Petersburg ballet tradition.
  • E. Ludmila Bragina
    Ludmila Bragina is a former Soviet middle-distance runner best known for winning Olympic gold and setting multiple world records in the 1500 metres in the early 1970s.
  • 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_69d889e1030481909950e140c63255b9 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e469ead59c8190a06519311891af3c completed April 19, 2026, 5:36 a.m.
Created at: April 10, 2026, 5:51 a.m.