Triple

T6632275
Position Surface form Disambiguated ID Type / Status
Subject Holly Golightly E149954 entity
Predicate loveInterestOf P7325 FINISHED
Object Paul Varjak E149954 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: Paul Varjak | Statement: [Holly Golightly, loveInterestOf, Paul Varjak]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul Varjak
Context triple: [Holly Golightly, loveInterestOf, Paul Varjak]
  • A. Paul Varjak chosen
    Paul Varjak is a struggling writer and Holly Golightly’s neighbor and love interest in Truman Capote’s novella and the film adaptation "Breakfast at Tiffany’s."
  • B. Branko Lustig
    Branko Lustig was a Croatian film producer and Holocaust survivor best known for his Academy Award–winning work on major historical epics such as Schindler’s List and Gladiator.
  • C. Paul Tabori
    Paul Tabori was a Hungarian-British writer, journalist, and screenwriter known for his work in mid-20th-century film and literature, often exploring psychological and speculative themes.
  • D. Victor Kugler
    Victor Kugler was one of the Dutch helpers who risked his life to hide Anne Frank and her family during the Nazi occupation of the Netherlands.
  • E. Viktor Kaplan
    Viktor Kaplan was an Austrian engineer best known for inventing the Kaplan turbine, a highly efficient water turbine widely used in hydroelectric power plants.
  • 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_69c687ee50048190aa151765bef16193 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6afc9138c81909d228ce4936d6b8b completed March 27, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6e4518f4881909c0a56df993d2af6 completed March 27, 2026, 8:10 p.m.
Created at: March 27, 2026, 1:59 p.m.