Triple

T22100767
Position Surface form Disambiguated ID Type / Status
Subject Passport to Pimlico E546165 entity
Predicate starredActor P5563 FINISHED
Object Sydney Tafler 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: Sydney Tafler | Statement: [Passport to Pimlico, starredActor, Sydney Tafler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sydney Tafler
Context triple: [Passport to Pimlico, starredActor, Sydney Tafler]
  • A. Sydney Tafler chosen
    Sydney Tafler was a British character actor known for his prolific film and television work from the 1940s to the 1970s, often portraying sharp-talking or streetwise figures.
  • B. Alexandra Papenfus
    Alexandra Papenfus is a person after whom another individual named Alexandra was named, suggesting she holds personal or familial significance to the namer.
  • C. Juliana Hatkoff
    Juliana Hatkoff is a children's book coauthor known for collaborating with her father, investor and philanthropist Craig Hatkoff, on inspirational animal stories.
  • D. Samantha Nisenboim
    Samantha Nisenboim is a film producer known for her work on the 2023 horror-comedy movie "Renfield."
  • E. Alexandra Scherer
    Alexandra Scherer is a German local politician who serves as the mayor of the spa town Bad Wurzach in Baden-Württemberg.
  • 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_69e11e378dc08190896d6a51597afd5a completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1291501508190ad5689be5abb2ba6 completed April 28, 2026, 9:39 p.m.
Created at: April 16, 2026, 8:30 p.m.