Triple

T6339984
Position Surface form Disambiguated ID Type / Status
Subject Dmytro E142599 entity
Predicate hasShortForm P43 FINISHED
Object Dmytryk E318248 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: Dmytryk | Statement: [Dmytro, hasShortForm, Dmytryk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dmytryk
Context triple: [Dmytro, hasShortForm, Dmytryk]
  • A. Janusz Kamiński
    Janusz Kamiński is a Polish-born, Academy Award–winning cinematographer best known for his long-standing collaboration with director Steven Spielberg on films such as Schindler’s List and Saving Private Ryan.
  • B. Anatole Litvak
    Anatole Litvak was a Ukrainian-born film director known for his work in Hollywood and Europe, particularly for psychologically intense dramas and wartime films.
  • C. Abraham Polonsky chosen
    Abraham Polonsky was an American screenwriter and director known for his socially conscious, politically charged films and for being blacklisted during the Hollywood Red Scare.
  • D. Józef Czapski
    Józef Czapski was a Polish painter, writer, and intellectual known for his memoirs of Soviet captivity and his role in documenting the fate of Polish officers during and after World War II.
  • E. Michel Litvak
    Michel Litvak is a film producer known for financing and producing a range of Hollywood movies through his company, often focusing on high-concept thrillers and action films.
  • 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_69c008d5ab108190b346c465696824a9 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06741fbbc81908d947182b197bf59 completed March 22, 2026, 10:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69c604352f148190b5accc28462256ad completed March 27, 2026, 4:14 a.m.
Created at: March 22, 2026, 4:30 p.m.